Robot–City Interaction: Mapping the Research Landscape—A Survey of the Interactions Between Robots and Modern Cities
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paper_title: Cooperative autonomous driving: intelligent vehicles sharing city roads

paper_content:

The paper presents the Intelligent Control System Laboratory's (ICSL) Cooperative Autonomous Mobile Robot technologies and their application to intelligent vehicles for cities. The deployed decision and control algorithms made the road-scaled vehicles capable of undertaking cooperative autonomous maneuvers. Because the focus of ICSL's research is in decision and control algorithms, it is therefore reasonable to consider replacing or upgrading the sensors used with more recent road sensory concepts as produced by other research groups. While substantial progress has been made, there are still some issues that need to be addressed such as: decision and control algorithms for navigating roundabouts, real-time integration of all data, and decision-making algorithms to enable intelligent vehicles to choose the driving maneuver as they go. With continued research, it is feasible that cooperative autonomous vehicles will coexist alongside human drivers in the not-too-distant future.
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paper_title: Social geographies II: Robots

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This report examines how social geographers are engaging with the questions that robots and robotic technologies provoke. First, it discusses Marxist analyses of machines and troubles the role that robots play in social production and reproduction. Second, robots as actors in assemblages of sociospatial relations are interrogated for their role in state violence. Third, the dynamic change brought about by smart cities and their algorithmic subjects is discussed. The concluding section is speculative, discussing robots and the ethics of care. This report asks social geographers to reimagine their social geographies in relation to the role of robots in everyday life.
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paper_title: Enabling intelligent energy management for robots using publicly available maps

paper_content:

Energy consumption represents one of the most basic constraints for mobile robot autonomy. We propose a new framework to predict energy consumption using information extracted from publicly available maps. This method avoids having to model internal robot configurations, which are often unavailable, while still providing invaluable predictions for both explored and unexplored trajectories. Our approach uses a heteroscedastic Gaussian Process to model the power consumption, which explicitly accounts for variance due to exogenous latent factors such as traffic and weather conditions. We evaluate our framework on 30km of data collected from a city centre environment with a mobile robot travelling on pedestrian walkways. Results across five different test routes show an average difference between predicted and measured power consumption of 3.3%, leading to an average error of 6.6% on predictions of energy consumption. The distinct advantage of our model is our ability to predict measurement variance. The variance predictions improved by 84.3% over a benchmark.
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paper_title: Methodological framework of sustainability assessment in City Sustainability Index (CSI): A concept of constraint and maximisation indicators

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Abstract This paper presents a framework of City Sustainability Index (CSI) incorporating indicators in the environmental, economic and social dimensions. We define a sustainable city as the spatial entity that maximises the benefits in economic and social dimensions under relevant constraints on environmental limitations and socio-economic distributional equity. Based on the definition, we provide five expressive forms as a framework for judging city sustainability, using a concept of two types of indicators: constraint and maximisation indicators. Constraint indicators judge sustainability of cities based on relevant criteria in terms of environmental sustainability and socio-economic distributional justice. Maximisation indicators measure the benefits cities produce in economic and social aspects. Indicators in the three dimensions – environmental, economic and social indicators – can be categorised into the two types of indicators. In conclusion, we need to assess the two dimensions of cities – limitations and benefits – independently without offsetting one against the other in terms of strong sustainability.
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paper_title: A survey on IEEE 802 . 11 ah : An enabling networking technology for smart cities

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We study carefully the IEEE 802.11ah draft standard published in July 2014.We overview use cases of .11ah, especially related to smart cities scenarios.We describe in details novel mechanisms and explain why they are needed in .11ah. Smart technologies play a key role in sustainable economic growth. They transform houses, offices, factories, and even cities into autonomic, self-controlled systems acting often without human intervention and thus sparing people routine connected with information collecting and processing. The paper gives an overview of a novel Wi-Fi technology, currently under development, which aims to organize communication between various devices used in such applications as smart grids, smart meters, smart houses, smart healthcare systems, smart industry, etc.
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paper_title: A Smart City Initiative: the Case of Barcelona

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Information and communication technology is changing the way in which cities organise policymaking and urban growth. Smart Cities base their strategy on the use of information and communication technologies in several fields such as economy, environment, mobility and governance to transform the city infrastructure and services. This paper draws on the city of Barcelona and intends to analyse its transformation from a traditional agglomeration to a twenty-first century metropolis. The case of Barcelona is of special interest due to its apparent desire, reflected by its current policies regarding urban planning, to be considered as a leading metropolis in Europe. Hence, an assessment of the Smart City initiative will cast light on the current status of Barcelona’s urban policy and its urban policy of Barcelona and its future directions. This article analyses Barcelona’s transformation in the areas of Smart City management; drivers, bottlenecks, conditions and assets. First, it presents the existing literature on Barcelona’s Smart City initiative. Then, the case study analysis is presented with the Barcelona Smart City model. After describing this model, we further explore the main components of the Smart City strategy of Barcelona in terms of Smart districts, living labs, initiatives, e-Services, infrastructures and Open Data. This paper also reveals certain benefits and challenges related to this initiative and its future directions. The results of the case study analysis indicate that Barcelona has been effectively implementing the Smart City strategy with an aim to be a Smart City model for the world.
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paper_title: Probabilistic collision state checker for crowded environments

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For path planning algorithms of robots it is important that the robot does not reach a state of inevitable collision. In crowded environments with many humans or robots, the set of possible inevitable collision states (ICS) is often unacceptably high, such that the robot has to stop and wait in too many situations. For this reason, the concept of ICS is extended to probabilistic collision states (PCS), which estimates the collision probability for a given state. This allows to efficiently run planning algorithms through crowded environments when accepting a certain collision probability. A further novelty is that the obstacles possibly react to the robot in order to mitigate the risk of a collision. The results show a significant difference in interaction behavior. Thus, this approach is especially suited for active and non-deterministic moving obstacles in the robot workspace.
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paper_title: Semantic Modelling of Smart City Data

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Recent advancements in communication technologies for providing ubiquitous Internet access as well as advancements on reduction of cost and form-factor of mobile devices and sensors are seen as an enabler for the Internet of Things (IoT). The industry predicts an interconnected world of 50 billion devices by 20201. The Web of Things (WoT) relies on the connectivity service of IoT to create services and applications exploiting the IoT data [1]. Cities present an opportunity for rendering WoT-enabled services. According to the World Health Organization, population in cities will double by the middle of this century2, while cities deal with increasingly pressing issues such as environmental sustainability, economic growth and citizen mobility. In this paper, we propose a discussion around the need for common semantic descriptions for smart city data to facilitate future services in “smart cities”. We present examples of data that can be collected from cities, discuss issues around this data and put forward some preliminary thoughts for creating a semantic description model to describe and help discover, index and query smart city data.
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paper_title: Towards a science of integrated AI and Robotics

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The early promise of the impact of machine intelligence did not involve the partitioning of the nascent field of Artificial Intelligence. The founders of AI envisioned the notion of embedded intell ...
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paper_title: The Real-Time City? Big Data and Smart Urbanism

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‘Smart cities’ is a term that has gained traction in academia, business and government to describe cities that, on the one hand, are increasingly composed of and monitored by pervasive and ubiquitous computing and, on the other, whose economy and governance is being driven by innovation, creativity and entrepreneurship, enacted by smart people. This paper focuses on the former and, drawing on a number of examples, details how cities are being instrumented with digital devices and infrastructure that produce ‘big data’. Such data, smart city advocates argue enables real-time analysis of city life, new modes of urban governance, and provides the raw material for envisioning and enacting more efficient, sustainable, competitive, productive, open and transparent cities. The final section of the paper provides a critical reflection on the implications of big data and smart urbanism, examining five emerging concerns: the politics of big urban data, technocratic governance and city development, corporatisation of city governance and technological lock-ins, buggy, brittle and hackable cities, and the panoptic city.
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paper_title: A Smart City Initiative: the Case of Barcelona

paper_content:

Information and communication technology is changing the way in which cities organise policymaking and urban growth. Smart Cities base their strategy on the use of information and communication technologies in several fields such as economy, environment, mobility and governance to transform the city infrastructure and services. This paper draws on the city of Barcelona and intends to analyse its transformation from a traditional agglomeration to a twenty-first century metropolis. The case of Barcelona is of special interest due to its apparent desire, reflected by its current policies regarding urban planning, to be considered as a leading metropolis in Europe. Hence, an assessment of the Smart City initiative will cast light on the current status of Barcelona’s urban policy and its urban policy of Barcelona and its future directions. This article analyses Barcelona’s transformation in the areas of Smart City management; drivers, bottlenecks, conditions and assets. First, it presents the existing literature on Barcelona’s Smart City initiative. Then, the case study analysis is presented with the Barcelona Smart City model. After describing this model, we further explore the main components of the Smart City strategy of Barcelona in terms of Smart districts, living labs, initiatives, e-Services, infrastructures and Open Data. This paper also reveals certain benefits and challenges related to this initiative and its future directions. The results of the case study analysis indicate that Barcelona has been effectively implementing the Smart City strategy with an aim to be a Smart City model for the world.
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paper_title: Toward a framework for levels of robot autonomy in human-robot interaction

paper_content:

Autonomy is a critical construct related to human-robot interaction (HRI) and varies widely across robot platforms. Levels of robot autonomy (LORA), ranging from teleoperation to fully autonomous systems, influence the way in which humans and robots interact with one another. Thus, there is a need to understand HRI by identifying variables that influence---and are influenced by---robot autonomy. Our overarching goal is to develop a framework for LORA in HRI. To reach this goal, our framework draws links between HRI and human-automation interaction, a field with a long history of studying and understanding human-related variables. The construct of autonomy is reviewed and redefined within the context of HRI. Additionally, this framework proposes a process for determining a robot's autonomy level by categorizing autonomy along a 10-point taxonomy. The framework is intended to be treated as a guideline for determining autonomy, categorizing the LORA along a qualitative taxonomy and considering HRI variables (e.g., acceptance, situation awareness, reliability) that may be influenced by the LORA.
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paper_title: Will the real smart city please stand up ? Intelligent , progressive or entrepreneurial ?

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Debates about the future of urban development in many Western countries have been increasingly influenced by discussions of smart cities. Yet despite numerous examples of this ‘urban labelling’ phenomenon, we know surprisingly little about so‐called smart cities, particularly in terms of what the label ideologically reveals as well as hides. Due to its lack of definitional precision, not to mention an underlying self‐congratulatory tendency, the main thrust of this article is to provide a preliminary critical polemic against some of the more rhetorical aspects of smart cities. The primary focus is on the labelling process adopted by some designated smart cities, with a view to problematizing a range of elements that supposedly characterize this new urban form, as well as question some of the underlying assumptions/contradictions hidden within the concept. To aid this critique, the article explores to what extent labelled smart cities can be understood as a high‐tech variation of the ‘entrepreneurial city’...
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paper_title: Key Concepts in Urban Studies

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The SAGE Key Concepts series provides students with accessible and authoritative knowledge of the essential topics in a variety of disciplines. Cross-referenced throughout, the format encourages critical evaluation through understanding. ::: ::: Written by experienced and respected academics, the books are indispensable study aids and guides to comprehension. ::: ::: Key Concepts in Urban Studies: ::: ::: Clearly and concisely explains the basic ideas in the interdisciplinary field of urban studies ::: ::: Offers concise discussions of concepts ranging from community, neighbourhood, and the city to globalization, the New Urbanism, feminine space, and urban problems ::: ::: Constitutes a re-examination of the key ideas in the field ::: ::: Is illustrated throughout with international examples ::: ::: Provides an essential reference guide for all students and teachers across the urban disciplines within sociology, political science, planning and geography.
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paper_title: Urbanism as A Way of Life

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Our aim is to find out about the urbanism as a way in modern life, how it was influenced in human life in a city and how it became a dependent variable. Specifically we mentioned about the author Louis Wirth who gave an important essay on urbanism a way of life. Mentioned how it inspired other urban sociologists to analyze the development of new urban lifestyles and to compare suburban life styles.
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paper_title: The Social Science Encyclopedia

paper_content:

* Abnormal Psychology * Accounting * Adolescence * Advertising * Anarchism * Anthropology * Archaeology * Aristotle * Banking * Behaviourism * Jeremy Bentham * Business Studies * Cannibalism * Capital Punishment * Capitalism * Child Care * Noam Chomsky * Communications * Communism * Conservatism * Corporate Enterprise * Criminology * Cultural History * Charles Darwin * Democracy * Divorce * Drug Use * Eating Disorders * Economics * Education * Environment * Family * Feminist Theory * Sigmund Freud * Gender and Sex * Geography * History * David Hume * Incest * Individualism * International Relations * Interviews and Interviewing * Judicial Process * John Maynard Keynes * Language and Culture * Law * Libido * Linguistics * Machiavelli * Karl Marx * Media and Politics * Memory * Mental Health * Mortality * Nature * Orientalism * Patriarchy * Peasants * Penology * Political Theory * Power * Psychology * Punishment * Racism * Religion and Ritual * Sexual Behaviour * Sociology * Sport * Taboo * Taxation * Urban Planning * Violence * Voting * War Studies * Welfare State * Wittgenstein * Work and Leisure
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paper_title: A Communication Robot in a Shopping Mall

paper_content:

This paper reports our development of a communication robot for use in a shopping mall to provide shopping information, offer route guidance, and build rapport. In the development, the major difficulties included sensing human behaviors, conversation in a noisy daily environment, and the needs of unexpected miscellaneous knowledge in the conversation. We chose a network-robot system approach, where a single robot's poor sensing capability and knowledge are supplemented by ubiquitous sensors and a human operator. The developed robot system detects a person with floor sensors to initiate interaction, identifies individuals with radio-frequency identification (RFID) tags, gives shopping information while chatting, and provides route guidance with deictic gestures. The robot was partially teleoperated to avoid the difficulty of speech recognition as well as to furnish a new kind of knowledge that only humans can flexibly provide. The information supplied by a human operator was later used to increase the robot's autonomy. For 25 days in a shopping mall, we conducted a field trial and gathered 2642 interactions. A total of 235 participants signed up to use RFID tags and, later, provided questionnaire responses. The questionnaire results are promising in terms of the visitors' perceived acceptability as well as the encouragement of their shopping activities. The results of the teleoperation analysis revealed that the amount of teleoperation gradually decreased, which is also promising.
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paper_title: Autonomous repositioning and localization of an in situ fabricator

paper_content:

Despite the prevalent use of robotic technologies in industrial manufacturing, their use on building construction sites is still very limited. This is mainly due to the unstructured nature of construction sites and the fact that the structures built must be larger than the machines which build them. This paper addresses these difficulties by presenting a repositioning and localization system which, using purely on-board sensing, allows a mobile robot to maintain a high degree of end-effector positioning accuracy while moving among numerous building positions during a building task. We introduce a newly developed machine, called the In situ Fabricator (IF), whose goal is to bring digital fabrication to the construction site. The capabilities of the repositioning and localization system is demonstrated through the construction of a vertical stack of bricks, in which the IF repositions itself after placing each brick. With this experiment, we demonstrate that the IF can build with sub-centimeter accuracy over long building sequences.
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paper_title: Toward a framework for levels of robot autonomy in human-robot interaction

paper_content:

Autonomy is a critical construct related to human-robot interaction (HRI) and varies widely across robot platforms. Levels of robot autonomy (LORA), ranging from teleoperation to fully autonomous systems, influence the way in which humans and robots interact with one another. Thus, there is a need to understand HRI by identifying variables that influence---and are influenced by---robot autonomy. Our overarching goal is to develop a framework for LORA in HRI. To reach this goal, our framework draws links between HRI and human-automation interaction, a field with a long history of studying and understanding human-related variables. The construct of autonomy is reviewed and redefined within the context of HRI. Additionally, this framework proposes a process for determining a robot's autonomy level by categorizing autonomy along a 10-point taxonomy. The framework is intended to be treated as a guideline for determining autonomy, categorizing the LORA along a qualitative taxonomy and considering HRI variables (e.g., acceptance, situation awareness, reliability) that may be influenced by the LORA.
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paper_title: The STRANDS Project: Long-Term Autonomy in Everyday Environments

paper_content:

Thanks to the efforts of the robotics and autonomous systems community, the myriad applications and capacities of robots are ever increasing. There is increasing demand from end users for autonomous service robots that can operate in real environments for extended periods. In the Spatiotemporal Representations and Activities for Cognitive Control in Long-Term Scenarios (STRANDS) project (http://strandsproject.eu), we are tackling this demand head-on by integrating state-of-the-art artificial intelligence and robotics research into mobile service robots and deploying these systems for long-term installations in security and care environments. Our robots have been operational for a combined duration of 104 days over four deployments, autonomously performing end-user-defined tasks and traversing 116 km in the process. In this article, we describe the approach we used to enable long-term autonomous operation in everyday environments and how our robots are able to use their long run times to improve their own performance.
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paper_title: Cooperative autonomous driving: intelligent vehicles sharing city roads

paper_content:

The paper presents the Intelligent Control System Laboratory's (ICSL) Cooperative Autonomous Mobile Robot technologies and their application to intelligent vehicles for cities. The deployed decision and control algorithms made the road-scaled vehicles capable of undertaking cooperative autonomous maneuvers. Because the focus of ICSL's research is in decision and control algorithms, it is therefore reasonable to consider replacing or upgrading the sensors used with more recent road sensory concepts as produced by other research groups. While substantial progress has been made, there are still some issues that need to be addressed such as: decision and control algorithms for navigating roundabouts, real-time integration of all data, and decision-making algorithms to enable intelligent vehicles to choose the driving maneuver as they go. With continued research, it is feasible that cooperative autonomous vehicles will coexist alongside human drivers in the not-too-distant future.
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paper_title: Context-based detection of pedestrian crossing intention for autonomous driving in urban environments

paper_content:

This paper focuses on the detection of pedestrian crossing intention to improve the situation awareness for autonomous driving in urban environments. A new definition of pedestrian crossing intention is discussed, which allows self-driving vehicles to identify pedestrians, whose intended actions are relevant for the own behavior planning, at an early stage. We propose a context-based feature descriptor in combination with a SVM classifier for detecting this. The descriptor captures the movement of a pedestrian relative to the road and the spatial layout of other scene elements in a generic manner. The performance of the feature descriptor is evaluated in relation to various SVM setups. Feasibility of the approach is demonstrated with data captured on-board of a vehicle in real inner-city traffic. The evaluation of the classification results confirms, that context-based data is a promising indicator for pedestrian crossing intention and that the proposed feature descriptor is capable of representing this. It is further shown that a lack of information about the pedestrian's posture and body movement results in a delayed detection of the pedestrians changing their crossing intention when compared to a human observer.
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paper_title: Neel: an intelligent shopping guide - using web data for rich interactions

paper_content:

The project Myneel and its portal myneel.com together were envisaged to provide us with crucial insights into the commercialization of service robots. In this paper we describe our system and propose an approach to develop an interactive conversational agent which can serve shopping needs of the visitors in a shopping mall.
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paper_title: Sharing the Road: Autonomous Vehicles Meet Human Drivers

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In modern urban settings, automobile traffic and collisions lead to endless frustration as well as significant loss of life, property, and productivity. Recent advances in artificial intelligence suggest that autonomous vehicle navigation may soon be a reality. In previous work, we have demonstrated that a reservation-based approach can efficiently and safely govern interactions of multiple autonomous vehicles at intersections. Such an approach alleviates many traditional problems associated with intersections, in terms of both safety and efficiency. However, the system relies on all vehicles being equipped with the requisite technology-a restriction that would make implementing such a system in the real world extremely difficult. In this paper, we extend this system to allow for incremental deployability. The modified system is able to accommodate traditional human-operated vehicles using existing infrastructure. Furthermore, we show that as the number of autonomous vehicles on the road increases, traffic delays decrease monotonically toward the levels exhibited in our previous work. Finally, we develop a method for switching between various human-usable configurations while the system is running, in order to facilitate an even smoother transition. The work is fully implemented and tested in our custom simulator, and we present detailed experimental results attesting to its effectiveness.
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paper_title: Human-Robot Interaction in Public and Smart Spaces

paper_content:

We have developed a “network robot system” framework with the objective of enabling practical deployment of social robots to provide real-world services in everyday social environments. This framework addresses practical issues in social human-robot interaction by integrating ambient intelligence systems, networked data stores, human supervisors, and centralized planning. All of the elements of the system have been developed and tested in public and commercial spaces such as shopping malls, resulting in a flexible robot control architecture based on practical, real-world requirements. We describe several elements of the system and demonstrate examples of its use in five years of real-world field deployments and research. Finally, we present the Ubiquitous Network Robot Platform (UNR-PF), an internationally-standardized high-level architecture for service robots based on our framework.
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paper_title: A Cloud Based Service for Management and Planning of Autonomous UAV Missions in Smart City Scenarios

paper_content:

Cloud Robotics is an emerging paradigm in which robots, seen as abstract agents, have the possibility to connect to a common network and share on a complex infrastructure the information and knowledge they gather about the physical world; or conversely consume the data collected by other agents or made available on accessible database and repositories. In this paper we propose an implementation of an emergency-management service exploiting the possibilities offered by cloud robotics in a smart city scenario. A high-level cloud-platform manages a number of unmanned aerial vehicles (quadrotor UAVs) with the goal of providing aerial support to citizens that require it via a dedicated mobile app. The UAV reaches the citizen while forwarding a real-time video streaming to a privileged user (police officer),connected to the same cloud platform, that is allowed to teleoperate it by remote.
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paper_title: Mobile robotic fabrication on construction sites: DimRob

paper_content:

In this paper, viable applications for mobile robotic units on construction sites are explored. While identifying potential areas for in-situ fabrication in the construction sector, the intention is also to build upon innovative man-machine interaction paradigms to deal with the imprecision and tolerances often faced on construction sites. By combining the precision of the machine with the innate cognitive human skills, a simple but effective mobile fabrication system is tested for the building of algorithmically designed structures that would not be possible through conventional manual means. It is believed that this new approach to man-machine collaboration, aimed at a deeper integration of human ability with the strengths of digitally controlled machines, will result in advances in the construction sector, thus opening up new design and application fields for architects and planners.
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paper_title: Precise and efficient model-based vehicle tracking method using Rao-Blackwellized and scaling series particle filters

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A precise and efficient tracking technique is essential for an intelligent vehicle to interact with the surrounding vehicles on the road. In this paper, we propose a model-based vehicle tracking method using the Rao-Blackwellized particle filter (RBPF) and scaling series particle filter (SSPF).
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paper_title: EureCar turbo: A self-driving car that can handle adverse weather conditions

paper_content:

Autonomous driving technology has made significant advances in recent years. In order for self-driving cars to become practical, they are required to operate safely and reliably even under adverse driving conditions. However, most current autonomous driving cars have only been shown to be operational under amiable weather conditions, i.e., on sunny days on dry roads. In order to enable autonomous cars to handle adverse driving conditions such as rain and wet roads, the algorithm must be able to detect roads within a tolerable margin of error using sensors such as cameras and laser scanners. In this paper, we propose a sensor fusion algorithms that is able to operate under a variety of weather conditions, including rain. Our algorithm was validated when a strong shower occurred during the 2014 Hyundai Motor Company's Autonomous Car Competition. In this paper, we present the competition results that were collected on the same course on both sunny and rainy days. Based on the comparison, we propose the future directions to improve the autonomous driving capability under adverse environmental conditions.
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paper_title: The MuMMER project: Engaging human-robot interaction in real-world public spaces

paper_content:

MuMMER (MultiModal Mall Entertainment Robot) is a four-year, EU-funded project with the overall goal of developing a humanoid robot (SoftBank Robotics’ Pepper robot being the primary robot platform) with the social intelligence to interact autonomously and naturally in the dynamic environments of a public shopping mall, providing an engaging and entertaining experience to the general public. Using co-design methods, we will work together with stakeholders including customers, retailers, and business managers to develop truly engaging robot behaviours. Crucially, our robot will exhibit behaviour that is socially appropriate and engaging by combining speech-based interaction with non-verbal communication and human-aware navigation. To support this behaviour, we will develop and integrate new methods from audiovisual scene processing, social-signal processing, high-level action selection, and human-aware robot navigation. Throughout the project, the robot will be regularly deployed in Ideapark, a large public shopping mall in Finland. This position paper describes the MuMMER project: its needs, the objectives, R&D challenges and our approach. It will serve as reference for the robotics community and stakeholders about this ambitious project, demonstrating how a co-design approach can address some of the barriers and help in building follow-up projects.
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paper_title: The autonomous city explorer project: aims and system overview

paper_content:

As robots are gradually leaving highly structured factory environments and moving into human populated environments, they need to possess more complex cognitive abilities. Not only do they have to operate efficiently and safely in natural populated environments, but also be able to achieve higher levels of cooperation and interaction with humans. The autonomous city explorer (ACE) project envisions to create a robot that will autonomously navigate in an unstructured urban environment and find its way through interaction with humans. To achieve this, research results from the fields of autonomous navigation, path planning, environment modeling, and human-robot interaction are combined. In this paper a novel hardware platform is introduced, a system overview is given, the research foci of ACE are highlighted, approaches to the occurring challenges are proposed and analyzed, and finally some first results are presented.
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paper_title: Enabling intelligent energy management for robots using publicly available maps

paper_content:

Energy consumption represents one of the most basic constraints for mobile robot autonomy. We propose a new framework to predict energy consumption using information extracted from publicly available maps. This method avoids having to model internal robot configurations, which are often unavailable, while still providing invaluable predictions for both explored and unexplored trajectories. Our approach uses a heteroscedastic Gaussian Process to model the power consumption, which explicitly accounts for variance due to exogenous latent factors such as traffic and weather conditions. We evaluate our framework on 30km of data collected from a city centre environment with a mobile robot travelling on pedestrian walkways. Results across five different test routes show an average difference between predicted and measured power consumption of 3.3%, leading to an average error of 6.6% on predictions of energy consumption. The distinct advantage of our model is our ability to predict measurement variance. The variance predictions improved by 84.3% over a benchmark.
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paper_title: Watch this: Scalable cost-function learning for path planning in urban environments

paper_content:

In this work, we present an approach to learn cost maps for driving in complex urban environments from a very large number of demonstrations of driving behaviour by human experts. The learned cost maps are constructed directly from raw sensor measurements, bypassing the effort of manually designing cost maps as well as features. When deploying the learned cost maps, the trajectories generated not only replicate human-like driving behaviour but are also demonstrably robust against systematic errors in putative robot configuration. To achieve this we deploy a Maximum Entropy based, non-linear IRL framework which uses Fully Convolutional Neural Networks (FCNs) to represent the cost model underlying expert driving behaviour. Using a deep, parametric approach enables us to scale efficiently to large datasets and complex behaviours by being run-time independent of dataset extent during deployment. We demonstrate the scalability and the performance of the proposed approach on an ambitious dataset collected over the course of one year including more than 25k demonstration trajectories extracted from over 120km of driving around pedestrianised areas in the city of Milton Keynes, UK. We evaluate the resulting cost representations by showing the advantages over a carefully manually designed cost map and, in addition, demonstrate its robustness to systematic errors by learning precise cost-maps even in the presence of system calibration perturbations.
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paper_title: Road Traversability analysis using network properties of roadmaps

paper_content:

Traversability analysis is an important aspect of autonomous navigation in robotics. In this paper, we relate the idea of traversability to safety and ease of road usage by defining a novel sensor-data driven metric called Road Traversability Index (RTI). The RTI translate the geometric interaction of vehicle with road into a distance modulated index that can be used as advice for a human driver or an autonomous agent intending to traverse a particular road segment using a specific vehicle. We present a framework in which 3D sensor data is converted into a road model, which in turn is converted into a roadmap based motion planning graph to represent the underlying configuration space. The RTI is defined as a function of the roadmap by axiomatically satisfying all required properties of road traversability. We have tested our algorithmic framework on simulated scenarios to explore safety; and real-world data sets to discover aspects of traversability for vehicles of various types. Experimental results show that RTI is a practical tool that reveals information that may be hidden to human inspection or other methods of assessment that do not explicitly model a vehicle.
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paper_title: Autonomous Robot Navigation in Highly Populated Pedestrian Zones

paper_content:

In the past, there has been a tremendous amount of progress in the area of autonomous robot navigation, and a large variety of robots have been developed that demonstrated robust navigation capabilities indoors, in nonurban outdoor environments, or on roads; relatively few approaches have focused on navigation in urban environments such as city centers. Urban areas, however, introduce numerous challenges for autonomous robots as they are rather unstructured and dynamic. In this paper, we present a navigation system for mobile robots designed to operate in crowded city environments and pedestrian zones. We describe the different components of this system, including a simultaneous localization and mapping module for dealing with huge maps of city centers, a planning component for inferring feasible paths, taking into account the traversability and type of terrain, a module for accurate localization in dynamic environments, and the means for calibrating and monitoring the platform. Our navigation system has been implemented and tested in several large-scale field tests, in which a real robot autonomously navigated over several kilometers in a complex urban environment. This also included a public demonstration, during which the robot autonomously traveled along a more than 3-km-long route through the city center of Freiburg, Germany.
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paper_title: A navigation system for robots operating in crowded urban environments

paper_content:

Over the past years, there has been a tremendous progress in the area of robot navigation. Most of the systems developed thus far, however, are restricted to indoor scenarios, non-urban outdoor environments, or road usage with cars. Urban areas introduce numerous challenges to autonomous mobile robots as they are highly complex and in addition to that dynamic. In this paper, we present a navigation system for pedestrian-like autonomous navigation with mobile robots in city environments. We describe different components including a SLAM system for dealing with huge maps of city centers, a planning approach for inferring feasible paths taking also into account the traversability and type of terrain, and a method for accurate localization in dynamic environments. The navigation system has been implemented and tested in several large-scale field tests in which the robot Obelix managed to autonomously navigate from our university campus over a 3.3 km long route to the city center of Freiburg.
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paper_title: Field trial of an information-providing robot in a shopping mall

paper_content:

We developed an information-providing robot for a shopping mall. It moves around and hands over flyers about the mall and when people are interested or approach the robot to obtain some information, it starts the information-providing service. During the information-providing service, it provides directions and recommendations of shops in the mall. The robot is developed to be fully autonomous, but due to low performance in automatic speech recognition, this function is overtaken by a human operator. In our field trial, the robot worked for 53.4 hours (over 11 days) without any major failure (83.5% of time autonomously operated). We conducted interviews with visitors, and revealed that the majority of them found the information from the robot useful, and wanted to use it again.
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paper_title: ReFrESH: A self-adaptation framework to support fault tolerance in field mobile robots

paper_content:

Mobile robots are being employed far more often in extreme environments, such as urban search and rescue, with greater levels of autonomy; yet recent studies on field robotics show that numerous failure modes affect the reliability of the robot in meeting mission objectives. Therefore, fault tolerance is increasingly important for field robots operating in unpredictable environments to ensure safety and effectiveness of the system. This paper demonstrates a self-adaptation frame- work, ReFrESH, that contains mechanisms for fault detection and fault mitigation. The goal of ReFrESH is to provide diagnosable and maintainable infrastructure support, built into a real-time operating system, to manage task performance in the presence of unexpected uncertainties. ReFrESH augments the port-based object framework by attaching evaluation and estimation mechanisms to each functional component so that the robot can easily detect and locate faults. In conjunction, a task level decision mechanism interacts with the fault detection elements in order to generate and choose an optimal approach to mitigating faults. Moreover, to increase flexibility of the fault tolerance, ReFrESH provides self-adaptation support for both software and hardware functionality. To our knowledge, this is the first framework to support both software and hardware self- adaptation. A demonstrative application of ReFrESH illustrates its applicability through a target tracking task deployed on a mobile robot system.
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paper_title: Proactively Approaching Pedestrians with an Autonomous Mobile Robot in Urban Environments

paper_content:

This paper presents a trajectory planning method enabling autonomous robots to approach people in dynamic environments to initiate a conversation proactively. It is shown how integrating human inspired parameters in optimal control based motion planning enables people to predict and read the purpose of a motion more easily.
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paper_title: Map-optimized probabilistic traffic rule evaluation

paper_content:

Current traffic rule handling in autonomous driving relies on non-scalable methods such as explicitly hard-coding sets of logical statements to evaluate rules. This is sufficient for early prototypes but is not scalable for larger systems designed to work in arbitrary locations. Such methods can also become problematic when traversing different geographical entities with changing traffic rules. Additionally, they do not adequately convey the uncertainty of the traffic rule evaluation stemming from uncertainty in sensor measurements. We propose an exchangeable traffic rules module which takes a knowledge base of sentences in first-order logic as input. These sentences consist of a limited number of high-level queries which are independent of local jurisdiction (e.g. can I turn right?). The knowledge base is then compiled into a potentially large logic graph. However, only a relatively small subset of the knowledge base is relevant for specific road geometries (e.g. some of the rules applicable to an intersection is not relevant for a T-junction). Since detailed road maps are available for autonomous driving, this information can be used to resolve these subsets in the knowledge base which only require map knowledge. Therefore, map information can be used to convert a single, large logic graph into a set of smaller, map-optimized logic graphs pruned for specific road geometries. The optimized graphs are then converted into Bayesian networks to facilitate probabilistic inference. Experiments were conducted using a traffic and scenario simulation framework. The results demonstrate a significant improvement in performance when using map-optimized logic graphs over a traditional first-order logic knowledge base.
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paper_title: Robots asking for directions: the willingness of passers-by to support robots

paper_content:

This paper reports about a human-robot interaction field trial conducted with the autonomous mobile robot ACE (Autonomous City Explorer) in a public place, where the ACE robot needs the support of human passers-by to find its way to a target location. Since the robot does not possess any prior map knowledge or GPS support, it has to acquire missing information through interaction with humans. The robot thus has to initiate communication by asking for the way, and retrieves information from passers-by showing the way by gestures (pointing) and marking goal positions on a still image on the touch screen of the robot. The aims of the field trial where threefold: (1) Investigating the aptitude of the navigation architecture, (2) Evaluating the intuitiveness of the interaction concept for the passers-by, (3) Assessing people's willingness to support the ACE robot in its task, i.e. assessing the social acceptability. The field trial demonstrates that the architecture enables successful autonomous path finding without any prior map knowledge just by route directions given by passers-by. An additional street survey and observational data moreover attests the intuitiveness of the interaction paradigm and the high acceptability of the ACE robot in the public place.
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paper_title: iCharibot: Design and Field Trials of a Fundraising Robot

paper_content:

In this work, we address the problem of increasing charitable donations through a novel, engaging fundraising robot: the Imperial Charity Robot (iCharibot). To better understand how to engage passers-by, we conducted a field trial in outdoor locations at a busy area in London, spread across 9 sessions of 40 minutes each. During our experiments, iCharibot attracted 679 people and engaged with 386 individuals. Our results show that interactivity led to longer user engagement with the robot. Our data further suggests both saliency and interactivity led to an increase in the total donation amount. These findings should prove useful for future design of robotic fundraisers in particular and for social robots in general.
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paper_title: Minotaurus: A System for Affective Human–Robot Interaction in Smart Environments

paper_content:

A service robot should be able to detect and identify the user in order to personalize its services and guarantee security, it should recognize the user’s emotions to allow affective interaction, and it should be able to communicate easily with the user and understand given commands by recognizing speech and gestures. Our research is motivated, for example, by the emerging needs of elderly care, health care, safety, and logistics. We have developed a distributed system for affective human–robot interaction which combines all the basic sensory elements and can collaborate with a smart environment and obtain further knowledge from the Internet. The realized HRI robot, Minotaurus, runs in real time and is capable of interacting with human beings. Minotaurus forms a rather generic platform for experimenting with human–robot collaboration in different applications and environments.
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paper_title: A roadwork scene signature based on the opponent colour model

paper_content:

The presence of roadworks greatly affects the validity of prior maps used for navigation by autonomous vehicles. This paper addresses the problem of quickly and robustly assessing the gist of traffic scenes for whether roadworks might be present. Without explicitly modelling individual roadwork indicators such as traffic cones, construction barriers or traffic signs, our method instead only exploits the engineered visual saliency of such objects. We draw inspiration from opponent colour vision in humans to formulate a novel roadwork scene signature based on an opponent spatial prior combined with gradient information. Finally, we apply our roadwork scene signature to the task of roadwork scene recognition, within a classification framework based on soft assignment vec-torization and RUSBoost. We evaluate our roadwork signature on real life data from our autonomous vehicle.
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paper_title: The effect of robot appearance types on motivating donation

paper_content:

According to the Hawthorne effect, when people feel someone staring at them, they tend to be moral because of psychological pressure. We applied this Hawthorne effect to the appearance design of robots and examined the effect of robot appearance types on motivating donation. We executed a 2 (appearance types: anthropomorphic vs. functional) within-participants experiment (N=20). Participants perceived more social presence to an anthropomorphic robot than a functional robot. In addition, participants were more willing to donate when interacting with an anthropomorphic robot than a functional robot. Categories and Subject Descriptors I.2.9 [Artificial Intelligence]: Robotics – commercial robots and applications; H.5.2 [Information Interfaces and Presentation]: User Interfaces – user-centered design
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paper_title: Common metrics for human-robot interaction

paper_content:

This paper describes an effort to identify common metrics for task-oriented human-robot interaction (HRI). We begin by discussing the need for a toolkit of HRI metrics. We then describe the framework of our work and identify important biasing factors that must be taken into consideration. Finally, we present suggested common metrics for standardization and a case study. Preparation of a larger, more detailed toolkit is in progress.
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paper_title: Human-Friendly Networked Partner Robots toward Sophisticated Services for A Community

paper_content:

This paper discusses the role of partner robots networked in SICE City. In order to realize sophisticated services for a community, the city design based on ubiquitous sensor network is very important. If a public office can be a service provider, service engineering can easily gather opinions of a resident as a user. A robot can be used as an interface connecting the physical world with the cyber world and as a human-friendly life-support system. Furthermore, the structurization of available environmental information is very important for robots interacting with humans. Robots can receive environmental information through the network from the environmental system. In this paper, we show several experimental results on the networked partner robots interacting with humans.
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paper_title: Simulation and control of an autonomous bucket excavator for landscaping tasks

paper_content:

Introducing autonomous machines to construction areas can improve many of the occurring processes. Therefore, this paper deals with problems in the field of creating an autonomous bucket excavator. A novel behavior-based approach for motion control is presented which allows natural boom trajectories, achieves good environment disturbance compensation behavior, guarantees safety of the movements concerning human beings and structures, and keeps a high extensibility of the system for future improvements. Furthermore, a simulation of soil deals as the basis for safe tests of the excavator's behavior in a simulated dynamic environment.
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paper_title: Intelligent cooperative control for urban tracking with Unmanned Air Vehicles

paper_content:

We introduce an intelligent cooperative control system for ground target tracking in a cluttered urban environment with a team of Unmanned Air Vehicles (UAVs). We extend the work of Yu et. al. [1] to add a machine learning component that uses observations of target position to learn a model of target motion. Our learner is the Sequence Memoizer [2], a Bayesian model for discrete sequence data, which we use to predict future target location identifiers, given a context of previous location identifiers. Simulated cooperative control of a team of 3 UAVs in a 100-block city filled with various sizes of buildings verifies that learning a model of target motion can improve target tracking performance.
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paper_title: Motion planning for autonomous vehicles in highly constrained urban environments

paper_content:

In this paper, we present a motion planning algorithm for autonomous navigation in highly constrained urban environments. Since common approaches to on-road trajectory planning turned out to be unsuitable for this task, we instead extended an A*-based planner originally designed for navigation in unstructured environments. Two novel node expansion methods were added to obtain smooth and accurate trajectories that consider the structure of the environment. The first one attempts to find a trajectory connecting the current node directly to the goal by solving a boundary value problem using numerical optimization. The second method leverages a simulated pure-pursuit controller to generate edges (i.e. short motion primitives) that guide the vehicle toward or along the global reference path. As a result, the planner is able to produce smooth paths while retaining the explorative power of A* that is needed to deal with challenging situations in urban driving (e.g., reversing in order to pass a vehicle that stopped unexpectedly). Its practical usefulness was demonstrated during extensive tests on an electric vehicle navigating a mock urban environment as well as on our own autonomous vehicle MuCAR-3.
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paper_title: Human and Computer Control of Undersea Teleoperators

paper_content:

Abstract : This is a review of factors pertaining to man-machine interaction in remote control of undersea vehicles, especially their manipulators and sensors. Emphasis is placed on human operator control of such teleoperator systems as a function of degree of automation, sensor-control integration and task demands for underwater search, object recovery and manipulation. Models of operator- computer performance are considered, particularly with respect to human supervisory control of semiautonomous systems. Sections of the report discuss: teleoperated submersible vehicles or work platforms; undersea tasks and how they can be analyzed; relative roles of human and computer or other control elements; control hardware (sensors, communication, propulsion, manipulation, control station) and how it affects the human controller; control software for computer- aided manipulation, including a review of various languages and algorithms presently available; human operator performance in manipulator control (a review of what we now know); present and prospective theoretical models of supervisory control; and finally, the needs for research in this area.
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paper_title: Dynamic obstacle avoidance approach for car-like robots in dynamic environments

paper_content:

In this paper, a new dynamic obstacle avoidance approach for nonholonomic mobile robots in dynamic environments is presented. In dynamic environments, the mobile robot is expected to encounter and safely avoid the obstacles along its way. This inevitably will delay the mobile robot in keeping to its original planned timeframe. To address this scenario, the proposed approach will ensure the mobile robot is able to gain the time lost during obstacle avoidance and reach the final point at the specified time. This approach is based on the dynamic trajectory planning scheme which utilized the replanning approach in order to avoid the obstacle. The performance of the proposed approach is tested through simulations in a simplified city-like dynamic environment.
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paper_title: Autonomous robotic system for bridge deck data collection and analysis

paper_content:

Bridge deck inspection is conducted to identify bridge condition deterioration and, thus, to facilitate implementation of appropriate maintenance or rehabilitation procedures. In this paper, we report the development of a robotic system for bridge deck data collection and analysis. The robotic system accurately localizes itself and autonomously maneuvers on the bridge deck to collect visual images and conduct nondestructive evaluation (NDE) measurements. The developed robotic system can reduce the cost and time of the bridge deck data collection. Crack detection and mapping algorithm to build the deck crack maps is presented in detail. The electrical resistivity (ER), impact-echo (IE) and ultrasonic surface waves (USW) data collected by the robot are analyzed to generate the corrosion, delamination and concrete elastic modulus maps of the deck. The presented robotic system has been successfully deployed to inspect numerous bridges.
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paper_title: Theory and evaluation of human robot interactions

paper_content:

Human-robot interaction (HRI) for mobile robots is still in its infancy. Most user interactions with robots have been limited to tele-operation capabilities where the most common interface provided to the user has been the video feed from the robotic platform and some way of directing the path of the robot. For mobile robots with semiautonomous capabilities, the user is also provided with a means of setting way points. More importantly, most HRI capabilities have been developed by robotics experts for use by robotics experts. As robots increase in capabilities and are able to perform more tasks in an autonomous manner we need to think about the interactions that humans will have with robots and what software architecture and user interface designs can accommodate the human in-the-loop. We also need to design systems that can be used by domain experts but not robotics experts. This paper outlines a theory of human-robot interaction and proposes the interactions and information needed by both humans and robots for the different levels of interaction, including an evaluation methodology based on situational awareness.
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paper_title: Visual industrial inspection using aerial robots

paper_content:

The use of unmanned aerial vehicles (UAV) offers a unique possibility to capture visual information in areas which are hard to reach or dangerous for humans. For UAVs to become a standard tool in visual inspection, it is of utmost importance that the aerial robot can be operated efficiently by a non-expert UAV pilot and that the navigation system is robust enough to remain operational in rough, industrial conditions. To this end, we present a UAV navigation system setup that uses visual-inertial sensor cues to estimate the UAV pose as well as to create a dense 3D map of the environment in real-time onboard the UAV, completely independent of GPS. The proposed navigation system enables the operator to directly interface the UAV using high-level commands such as waypoints or velocity commands while the navigation system ensures a stable and collision-free flight.
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paper_title: Leveraging Open Data for Supporting a Cloud Robotics Service in a Smart City Environment

paper_content:

At the dawn of cloud robotics , one of the biggest challenges is to successfully exploit the power offered by the internet for acquiring and sharing information, in order to build a common knowledge base among the agents. In this paper , we propose a cloud robotics service for emergency management in a smart city scenario. The application is capable of collecting significant open data over the internet. Then it uses them in the mission planning phase, in order to autonomously define a set of waypoints toward the target coordinates.
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paper_title: Energy optimal control to approach traffic lights

paper_content:

In this paper energy optimal solutions for the approach of red traffic lights are derived. As cars waste most of the fuel in city traffic and especially in queuing at traffic lights, the presented framework provides solutions to save fuel and to protect the environment. The solutions are obtained using the definition of spent physical work which has to be minimized. It covers both cases, that the time of switching of the traffic lights is known and that the time of switching can only be modeled as a stochastic process. For a known time of switching a continuous solution is derived using Pontryagin Minimum Principle; in the stochastic case a modified Bellmann equation is formulated. The latter is solved with dynamic programming techniques. The presented solutions can be used for autonomous driving as well as for driving assistant systems. Simulation results show the potential savings using the presented approach.
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paper_title: Ambient Intelligence: Technologies, Applications, and Opportunities

paper_content:

Ambient intelligence is an emerging discipline that brings intelligence to our everyday environments and makes those environments sensitive to us. Ambient intelligence (AmI) research builds upon advances in sensors and sensor networks, pervasive computing, and artificial intelligence. Because these contributing fields have experienced tremendous growth in the last few years, AmI research has strengthened and expanded. Because AmI research is maturing, the resulting technologies promise to revolutionarize daily human life by making people's surroundings flexible and adaptive. In this paper, we provide a survey of the technologies that comprise ambient intelligence and of the applications that are dramatically affected by it. In particular, we specifically focus on the research that makes AmI technologies ''intelligent''. We also highlight challenges and opportunities that AmI researchers will face in the coming years.
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paper_title: A Cloud Robotics Solution to Improve Social Assistive Robots for Active and Healthy Aging

paper_content:

Technological innovation in robotics and ICT represents an effective solution to tackle the challenge of providing social sustainable care services for the ageing population. The recent introduction of cloud technologies is opening new opportunities for the provisioning of advanced robotic services based on the cooperation of a number of connected robots, smart environments and devices improved by the huge cloud computational and storage capability. In this context, this paper aims to investigate and assess the potentialities of a cloud robotic system for the provisioning of assistive services for the promotion of active and healthy ageing. The system comprised two different smart environments, located in Italy and Sweden, where a service robot is connected to a cloud platform for the provisioning of localization based services to the users. The cloud robotic services were tested in the two realistic environments to assess the general feasibility of the solution and demonstrate the ability to provide assistive location based services in a multiple environment framework. The results confirmed the validity of the solution but also suggested a deeper investigation on the dependability of the communication technologies adopted in such kind of systems.
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paper_title: Adaptive patrolling by mobile robot for changing visitor trends

paper_content:

In this paper, a single mobile robot is used to patrol an indoor environment composed of rooms. The robot is required to monitor the rooms and detect visitors as many as possible. A key idea in the patrolling mission is to allow the robot to utilize information about visitor trends. Thus far, we have focused on a visiting probability as the trend. However, the visitor trends usually change over time. Therefore, the robot is further required to detect the changes and identify the correct visitor trends in each room. For this challenge, we present a novel change-point detection method. In this method, the Jensen-Shannon divergence is used as a dissimilarity measure between two distributions of the visiting probability. The change-point detection method is activated in the Bayesian learning for estimating the changed visiting probability. Consequently, the robot is allowed to adaptively patrol the changing environment. Through the simulation experiments, we discuss the effectiveness of the adaptive patrolling for the changes in the visitor trends.
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paper_title: Do you remember that shop?: computational model of spatial memory for shopping companion robots

paper_content:

We aim to develop a shopping companion robot that can share experience with users. In this study, we focused on the shared memory acquired when a robot walks together with a user. We developed a computational model of memory recall of visited locations in a shopping mall. The model was developed with data collection from 30 participants. We found that shop size, color intensity of facade, relative visibility, and time elapsed are the influencing features for recall. The model was used in a scenario of a shopping companion robot. The robot, Robovie, autonomously follows a user while inferring the user's memory recall of shops in the visited route. When the user asks the location of other shops, Robovie replied with destination description, referring to the known locations inferred with the model of the user's memory recall. With this scenario, we verified the effectiveness of the developed computational model of memory recall. The evaluation experiment revealed that the model outputs shops that the participants are likely to recall, and makes the directions given easier to understand.
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paper_title: Data science: challenges and directions

paper_content:

While it may not be possible to build a data brain identical to a human, data science can still aspire to imaginative machine thinking.
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paper_title: Development of a Socially Believable Multi-Robot Solution from Town to Home

paper_content:

Technological advances in the robotic and ICT fields represent an effective solution to address specific societal problems to support ageing and independent life. One of the key factors for these technologies is that they have to be socially acceptable and believable to the end-users. This paper aimed to present some technological aspects that have been faced to develop the Robot-Era system, a multi-robotic system that is able to act in a socially believable way in the environments daily inhabited by humans, such as urban areas, buildings and homes. In particular, this paper focuses on two services—shopping delivery and garbage collection—showing preliminary results on experiments conducted with 35 elderly people. The analysis adopts an end-user-oriented perspective, considering some of the main attributes of acceptability: usability, attitude, anxiety, trust and quality of life.
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paper_title: Searching for Smart City definition: a comprehensive proposal

paper_content:

During the latest years, smart city projects have been more and more popular and widespread all over the world. The continuous increasing of city’s population and the complexity of city management drive local governments towards the strong use of technologies to support a higher quality of urban spaces and a better offering of public services. The fascination of smart cities, able to link high technology, green environment and well-being for citizens, interests all the municipalities, independently on their dimensions, geographical area or culture. However, the concept of smart city is far from to be unambiguous. Several experiences all over the world show that cities define themselves as smart, but the meaning attributed to this word is different each time. Smart city concept has been growing from empirical experience, therefore a systemic theoretical study about this phenomenon still lacks. In this paper, the author aims to propose a comprehensive and verified definition of smart city, based on both a deep literature investigation about smart city studies and a large survey of smart city projects in the international panorama. The goal of this work is not only to provide a clear framework about this interesting and current topic, but also to support local governments and public administrations in effective smart city implementation, able to create public value and well being for citizens and environmental sustainability in the urban space.
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paper_title: Context-based detection of pedestrian crossing intention for autonomous driving in urban environments

paper_content:

This paper focuses on the detection of pedestrian crossing intention to improve the situation awareness for autonomous driving in urban environments. A new definition of pedestrian crossing intention is discussed, which allows self-driving vehicles to identify pedestrians, whose intended actions are relevant for the own behavior planning, at an early stage. We propose a context-based feature descriptor in combination with a SVM classifier for detecting this. The descriptor captures the movement of a pedestrian relative to the road and the spatial layout of other scene elements in a generic manner. The performance of the feature descriptor is evaluated in relation to various SVM setups. Feasibility of the approach is demonstrated with data captured on-board of a vehicle in real inner-city traffic. The evaluation of the classification results confirms, that context-based data is a promising indicator for pedestrian crossing intention and that the proposed feature descriptor is capable of representing this. It is further shown that a lack of information about the pedestrian's posture and body movement results in a delayed detection of the pedestrians changing their crossing intention when compared to a human observer.
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paper_title: Neel: an intelligent shopping guide - using web data for rich interactions

paper_content:

The project Myneel and its portal myneel.com together were envisaged to provide us with crucial insights into the commercialization of service robots. In this paper we describe our system and propose an approach to develop an interactive conversational agent which can serve shopping needs of the visitors in a shopping mall.
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paper_title: A Cloud Based Service for Management and Planning of Autonomous UAV Missions in Smart City Scenarios

paper_content:

Cloud Robotics is an emerging paradigm in which robots, seen as abstract agents, have the possibility to connect to a common network and share on a complex infrastructure the information and knowledge they gather about the physical world; or conversely consume the data collected by other agents or made available on accessible database and repositories. In this paper we propose an implementation of an emergency-management service exploiting the possibilities offered by cloud robotics in a smart city scenario. A high-level cloud-platform manages a number of unmanned aerial vehicles (quadrotor UAVs) with the goal of providing aerial support to citizens that require it via a dedicated mobile app. The UAV reaches the citizen while forwarding a real-time video streaming to a privileged user (police officer),connected to the same cloud platform, that is allowed to teleoperate it by remote.
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paper_title: Precise and efficient model-based vehicle tracking method using Rao-Blackwellized and scaling series particle filters

paper_content:

A precise and efficient tracking technique is essential for an intelligent vehicle to interact with the surrounding vehicles on the road. In this paper, we propose a model-based vehicle tracking method using the Rao-Blackwellized particle filter (RBPF) and scaling series particle filter (SSPF).
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paper_title: EureCar turbo: A self-driving car that can handle adverse weather conditions

paper_content:

Autonomous driving technology has made significant advances in recent years. In order for self-driving cars to become practical, they are required to operate safely and reliably even under adverse driving conditions. However, most current autonomous driving cars have only been shown to be operational under amiable weather conditions, i.e., on sunny days on dry roads. In order to enable autonomous cars to handle adverse driving conditions such as rain and wet roads, the algorithm must be able to detect roads within a tolerable margin of error using sensors such as cameras and laser scanners. In this paper, we propose a sensor fusion algorithms that is able to operate under a variety of weather conditions, including rain. Our algorithm was validated when a strong shower occurred during the 2014 Hyundai Motor Company's Autonomous Car Competition. In this paper, we present the competition results that were collected on the same course on both sunny and rainy days. Based on the comparison, we propose the future directions to improve the autonomous driving capability under adverse environmental conditions.
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paper_title: Enabling intelligent energy management for robots using publicly available maps

paper_content:

Energy consumption represents one of the most basic constraints for mobile robot autonomy. We propose a new framework to predict energy consumption using information extracted from publicly available maps. This method avoids having to model internal robot configurations, which are often unavailable, while still providing invaluable predictions for both explored and unexplored trajectories. Our approach uses a heteroscedastic Gaussian Process to model the power consumption, which explicitly accounts for variance due to exogenous latent factors such as traffic and weather conditions. We evaluate our framework on 30km of data collected from a city centre environment with a mobile robot travelling on pedestrian walkways. Results across five different test routes show an average difference between predicted and measured power consumption of 3.3%, leading to an average error of 6.6% on predictions of energy consumption. The distinct advantage of our model is our ability to predict measurement variance. The variance predictions improved by 84.3% over a benchmark.
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paper_title: Automated Parking Space Locator: RSM

paper_content:

The purpose of this project is to develop a Robotic Stall Monitor (RSM). This product will monitor parking spaces within an enclosed parking structure and wirelessly transmit data to a system where parking attendants may inform clients of available spaces. The project will focus on implementing a system travelling on an overhead track hosting numerous sensors capable of indicating if a stall is occupied. This project is funded by and done in collaboration with Federal APD.
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paper_title: ReFrESH: A self-adaptation framework to support fault tolerance in field mobile robots

paper_content:

Mobile robots are being employed far more often in extreme environments, such as urban search and rescue, with greater levels of autonomy; yet recent studies on field robotics show that numerous failure modes affect the reliability of the robot in meeting mission objectives. Therefore, fault tolerance is increasingly important for field robots operating in unpredictable environments to ensure safety and effectiveness of the system. This paper demonstrates a self-adaptation frame- work, ReFrESH, that contains mechanisms for fault detection and fault mitigation. The goal of ReFrESH is to provide diagnosable and maintainable infrastructure support, built into a real-time operating system, to manage task performance in the presence of unexpected uncertainties. ReFrESH augments the port-based object framework by attaching evaluation and estimation mechanisms to each functional component so that the robot can easily detect and locate faults. In conjunction, a task level decision mechanism interacts with the fault detection elements in order to generate and choose an optimal approach to mitigating faults. Moreover, to increase flexibility of the fault tolerance, ReFrESH provides self-adaptation support for both software and hardware functionality. To our knowledge, this is the first framework to support both software and hardware self- adaptation. A demonstrative application of ReFrESH illustrates its applicability through a target tracking task deployed on a mobile robot system.
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paper_title: Semantic interoperability for the Web of Things

paper_content:

This paper is co-authored by an informal group of experts from a broad range of backgrounds all of whom are active in standards groups, consortia and/or alliances in the Internet of Things (IoT) space. The ambition is to create mindshare on approaches to semantic interoperability and to actively encourage consensus building on what the co-authors regard as a key technical issue
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paper_title: Map-optimized probabilistic traffic rule evaluation

paper_content:

Current traffic rule handling in autonomous driving relies on non-scalable methods such as explicitly hard-coding sets of logical statements to evaluate rules. This is sufficient for early prototypes but is not scalable for larger systems designed to work in arbitrary locations. Such methods can also become problematic when traversing different geographical entities with changing traffic rules. Additionally, they do not adequately convey the uncertainty of the traffic rule evaluation stemming from uncertainty in sensor measurements. We propose an exchangeable traffic rules module which takes a knowledge base of sentences in first-order logic as input. These sentences consist of a limited number of high-level queries which are independent of local jurisdiction (e.g. can I turn right?). The knowledge base is then compiled into a potentially large logic graph. However, only a relatively small subset of the knowledge base is relevant for specific road geometries (e.g. some of the rules applicable to an intersection is not relevant for a T-junction). Since detailed road maps are available for autonomous driving, this information can be used to resolve these subsets in the knowledge base which only require map knowledge. Therefore, map information can be used to convert a single, large logic graph into a set of smaller, map-optimized logic graphs pruned for specific road geometries. The optimized graphs are then converted into Bayesian networks to facilitate probabilistic inference. Experiments were conducted using a traffic and scenario simulation framework. The results demonstrate a significant improvement in performance when using map-optimized logic graphs over a traditional first-order logic knowledge base.
---
paper_title: Minotaurus: A System for Affective Human–Robot Interaction in Smart Environments

paper_content:

A service robot should be able to detect and identify the user in order to personalize its services and guarantee security, it should recognize the user’s emotions to allow affective interaction, and it should be able to communicate easily with the user and understand given commands by recognizing speech and gestures. Our research is motivated, for example, by the emerging needs of elderly care, health care, safety, and logistics. We have developed a distributed system for affective human–robot interaction which combines all the basic sensory elements and can collaborate with a smart environment and obtain further knowledge from the Internet. The realized HRI robot, Minotaurus, runs in real time and is capable of interacting with human beings. Minotaurus forms a rather generic platform for experimenting with human–robot collaboration in different applications and environments.
---
paper_title: Cloud-Enhanced Robotic System for Smart City Crowd Control

paper_content:

Cloud robotics in smart cities is an emerging paradigm that enables autonomous robotic agents to communicate and collaborate with a cloud computing infrastructure. It complements the Internet of Things (IoT) by creating an expanded network where robots offload data-intensive computation to the ubiquitous cloud to ensure quality of service (QoS). However, offloading for robots is significantly complex due to their unique characteristics of mobility, skill-learning, data collection, and decision-making capabilities. In this paper, a generic cloud robotics framework is proposed to realize smart city vision while taking into consideration its various complexities. Specifically, we present an integrated framework for a crowd control system where cloud-enhanced robots are deployed to perform necessary tasks. The task offloading is formulated as a constrained optimization problem capable of handling any task flow that can be characterized by a Direct Acyclic Graph (DAG). We consider two scenarios of minimizing energy and time, respectively, and develop a genetic algorithm (GA)-based approach to identify the optimal task offloading decisions. The performance comparison with two benchmarks shows that our GA scheme achieves desired energy and time performance. We also show the adaptability of our algorithm by varying the values for bandwidth and movement. The results suggest their impact on offloading. Finally, we present a multi-task flow optimal path sequence problem that highlights how the robot can plan its task completion via movements that expend the minimum energy. This integrates path planning with offloading for robotics. To the best of our knowledge, this is the first attempt to evaluate cloud-based task offloading for a smart city crowd control system.
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paper_title: The Real-Time City? Big Data and Smart Urbanism

paper_content:

‘Smart cities’ is a term that has gained traction in academia, business and government to describe cities that, on the one hand, are increasingly composed of and monitored by pervasive and ubiquitous computing and, on the other, whose economy and governance is being driven by innovation, creativity and entrepreneurship, enacted by smart people. This paper focuses on the former and, drawing on a number of examples, details how cities are being instrumented with digital devices and infrastructure that produce ‘big data’. Such data, smart city advocates argue enables real-time analysis of city life, new modes of urban governance, and provides the raw material for envisioning and enacting more efficient, sustainable, competitive, productive, open and transparent cities. The final section of the paper provides a critical reflection on the implications of big data and smart urbanism, examining five emerging concerns: the politics of big urban data, technocratic governance and city development, corporatisation of city governance and technological lock-ins, buggy, brittle and hackable cities, and the panoptic city.
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paper_title: Improved GPS sensor model for mobile robots in urban terrain

paper_content:

Autonomous robot navigation in out-door scenarios gains increasing importance in various growing application areas. Whereas in non-urban domains such as deserts the problem of successful GPS-based navigation appears to be almost solved, navigation in urban domains particularly in the close vicinity of buildings is still a challenging problem. In such situations GPS accuracy significantly drops down due to multiple signal reflections with larger objects causing the so-called multipath error. In this paper we contribute a novel approach for incorporating multipath errors into the conventional GPS sensor model by analyzing environmental structures from online generated point clouds. The approach has been validated by experimental results conducted with an allterrain robot operating in scenarios requiring close-to-building navigation. Presented results show that positioning accuracy can significantly be improved within urban domains.
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paper_title: A Cloud Robotics Solution to Improve Social Assistive Robots for Active and Healthy Aging

paper_content:

Technological innovation in robotics and ICT represents an effective solution to tackle the challenge of providing social sustainable care services for the ageing population. The recent introduction of cloud technologies is opening new opportunities for the provisioning of advanced robotic services based on the cooperation of a number of connected robots, smart environments and devices improved by the huge cloud computational and storage capability. In this context, this paper aims to investigate and assess the potentialities of a cloud robotic system for the provisioning of assistive services for the promotion of active and healthy ageing. The system comprised two different smart environments, located in Italy and Sweden, where a service robot is connected to a cloud platform for the provisioning of localization based services to the users. The cloud robotic services were tested in the two realistic environments to assess the general feasibility of the solution and demonstrate the ability to provide assistive location based services in a multiple environment framework. The results confirmed the validity of the solution but also suggested a deeper investigation on the dependability of the communication technologies adopted in such kind of systems.
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paper_title: Data science: challenges and directions

paper_content:

While it may not be possible to build a data brain identical to a human, data science can still aspire to imaginative machine thinking.
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paper_title: A Communication Robot in a Shopping Mall

paper_content:

This paper reports our development of a communication robot for use in a shopping mall to provide shopping information, offer route guidance, and build rapport. In the development, the major difficulties included sensing human behaviors, conversation in a noisy daily environment, and the needs of unexpected miscellaneous knowledge in the conversation. We chose a network-robot system approach, where a single robot's poor sensing capability and knowledge are supplemented by ubiquitous sensors and a human operator. The developed robot system detects a person with floor sensors to initiate interaction, identifies individuals with radio-frequency identification (RFID) tags, gives shopping information while chatting, and provides route guidance with deictic gestures. The robot was partially teleoperated to avoid the difficulty of speech recognition as well as to furnish a new kind of knowledge that only humans can flexibly provide. The information supplied by a human operator was later used to increase the robot's autonomy. For 25 days in a shopping mall, we conducted a field trial and gathered 2642 interactions. A total of 235 participants signed up to use RFID tags and, later, provided questionnaire responses. The questionnaire results are promising in terms of the visitors' perceived acceptability as well as the encouragement of their shopping activities. The results of the teleoperation analysis revealed that the amount of teleoperation gradually decreased, which is also promising.
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paper_title: Autonomous repositioning and localization of an in situ fabricator

paper_content:

Despite the prevalent use of robotic technologies in industrial manufacturing, their use on building construction sites is still very limited. This is mainly due to the unstructured nature of construction sites and the fact that the structures built must be larger than the machines which build them. This paper addresses these difficulties by presenting a repositioning and localization system which, using purely on-board sensing, allows a mobile robot to maintain a high degree of end-effector positioning accuracy while moving among numerous building positions during a building task. We introduce a newly developed machine, called the In situ Fabricator (IF), whose goal is to bring digital fabrication to the construction site. The capabilities of the repositioning and localization system is demonstrated through the construction of a vertical stack of bricks, in which the IF repositions itself after placing each brick. With this experiment, we demonstrate that the IF can build with sub-centimeter accuracy over long building sequences.
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paper_title: The STRANDS Project: Long-Term Autonomy in Everyday Environments

paper_content:

Thanks to the efforts of the robotics and autonomous systems community, the myriad applications and capacities of robots are ever increasing. There is increasing demand from end users for autonomous service robots that can operate in real environments for extended periods. In the Spatiotemporal Representations and Activities for Cognitive Control in Long-Term Scenarios (STRANDS) project (http://strandsproject.eu), we are tackling this demand head-on by integrating state-of-the-art artificial intelligence and robotics research into mobile service robots and deploying these systems for long-term installations in security and care environments. Our robots have been operational for a combined duration of 104 days over four deployments, autonomously performing end-user-defined tasks and traversing 116 km in the process. In this article, we describe the approach we used to enable long-term autonomous operation in everyday environments and how our robots are able to use their long run times to improve their own performance.
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paper_title: Cooperative autonomous driving: intelligent vehicles sharing city roads

paper_content:

The paper presents the Intelligent Control System Laboratory's (ICSL) Cooperative Autonomous Mobile Robot technologies and their application to intelligent vehicles for cities. The deployed decision and control algorithms made the road-scaled vehicles capable of undertaking cooperative autonomous maneuvers. Because the focus of ICSL's research is in decision and control algorithms, it is therefore reasonable to consider replacing or upgrading the sensors used with more recent road sensory concepts as produced by other research groups. While substantial progress has been made, there are still some issues that need to be addressed such as: decision and control algorithms for navigating roundabouts, real-time integration of all data, and decision-making algorithms to enable intelligent vehicles to choose the driving maneuver as they go. With continued research, it is feasible that cooperative autonomous vehicles will coexist alongside human drivers in the not-too-distant future.
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paper_title: Sharing the Road: Autonomous Vehicles Meet Human Drivers

paper_content:

In modern urban settings, automobile traffic and collisions lead to endless frustration as well as significant loss of life, property, and productivity. Recent advances in artificial intelligence suggest that autonomous vehicle navigation may soon be a reality. In previous work, we have demonstrated that a reservation-based approach can efficiently and safely govern interactions of multiple autonomous vehicles at intersections. Such an approach alleviates many traditional problems associated with intersections, in terms of both safety and efficiency. However, the system relies on all vehicles being equipped with the requisite technology-a restriction that would make implementing such a system in the real world extremely difficult. In this paper, we extend this system to allow for incremental deployability. The modified system is able to accommodate traditional human-operated vehicles using existing infrastructure. Furthermore, we show that as the number of autonomous vehicles on the road increases, traffic delays decrease monotonically toward the levels exhibited in our previous work. Finally, we develop a method for switching between various human-usable configurations while the system is running, in order to facilitate an even smoother transition. The work is fully implemented and tested in our custom simulator, and we present detailed experimental results attesting to its effectiveness.
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paper_title: A Cloud Based Service for Management and Planning of Autonomous UAV Missions in Smart City Scenarios

paper_content:

Cloud Robotics is an emerging paradigm in which robots, seen as abstract agents, have the possibility to connect to a common network and share on a complex infrastructure the information and knowledge they gather about the physical world; or conversely consume the data collected by other agents or made available on accessible database and repositories. In this paper we propose an implementation of an emergency-management service exploiting the possibilities offered by cloud robotics in a smart city scenario. A high-level cloud-platform manages a number of unmanned aerial vehicles (quadrotor UAVs) with the goal of providing aerial support to citizens that require it via a dedicated mobile app. The UAV reaches the citizen while forwarding a real-time video streaming to a privileged user (police officer),connected to the same cloud platform, that is allowed to teleoperate it by remote.
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paper_title: Mobile robotic fabrication on construction sites: DimRob

paper_content:

In this paper, viable applications for mobile robotic units on construction sites are explored. While identifying potential areas for in-situ fabrication in the construction sector, the intention is also to build upon innovative man-machine interaction paradigms to deal with the imprecision and tolerances often faced on construction sites. By combining the precision of the machine with the innate cognitive human skills, a simple but effective mobile fabrication system is tested for the building of algorithmically designed structures that would not be possible through conventional manual means. It is believed that this new approach to man-machine collaboration, aimed at a deeper integration of human ability with the strengths of digitally controlled machines, will result in advances in the construction sector, thus opening up new design and application fields for architects and planners.
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paper_title: Precise and efficient model-based vehicle tracking method using Rao-Blackwellized and scaling series particle filters

paper_content:

A precise and efficient tracking technique is essential for an intelligent vehicle to interact with the surrounding vehicles on the road. In this paper, we propose a model-based vehicle tracking method using the Rao-Blackwellized particle filter (RBPF) and scaling series particle filter (SSPF).
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paper_title: The MuMMER project: Engaging human-robot interaction in real-world public spaces

paper_content:

MuMMER (MultiModal Mall Entertainment Robot) is a four-year, EU-funded project with the overall goal of developing a humanoid robot (SoftBank Robotics’ Pepper robot being the primary robot platform) with the social intelligence to interact autonomously and naturally in the dynamic environments of a public shopping mall, providing an engaging and entertaining experience to the general public. Using co-design methods, we will work together with stakeholders including customers, retailers, and business managers to develop truly engaging robot behaviours. Crucially, our robot will exhibit behaviour that is socially appropriate and engaging by combining speech-based interaction with non-verbal communication and human-aware navigation. To support this behaviour, we will develop and integrate new methods from audiovisual scene processing, social-signal processing, high-level action selection, and human-aware robot navigation. Throughout the project, the robot will be regularly deployed in Ideapark, a large public shopping mall in Finland. This position paper describes the MuMMER project: its needs, the objectives, R&D challenges and our approach. It will serve as reference for the robotics community and stakeholders about this ambitious project, demonstrating how a co-design approach can address some of the barriers and help in building follow-up projects.
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paper_title: Automated Parking Space Locator: RSM

paper_content:

The purpose of this project is to develop a Robotic Stall Monitor (RSM). This product will monitor parking spaces within an enclosed parking structure and wirelessly transmit data to a system where parking attendants may inform clients of available spaces. The project will focus on implementing a system travelling on an overhead track hosting numerous sensors capable of indicating if a stall is occupied. This project is funded by and done in collaboration with Federal APD.
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paper_title: Watch this: Scalable cost-function learning for path planning in urban environments

paper_content:

In this work, we present an approach to learn cost maps for driving in complex urban environments from a very large number of demonstrations of driving behaviour by human experts. The learned cost maps are constructed directly from raw sensor measurements, bypassing the effort of manually designing cost maps as well as features. When deploying the learned cost maps, the trajectories generated not only replicate human-like driving behaviour but are also demonstrably robust against systematic errors in putative robot configuration. To achieve this we deploy a Maximum Entropy based, non-linear IRL framework which uses Fully Convolutional Neural Networks (FCNs) to represent the cost model underlying expert driving behaviour. Using a deep, parametric approach enables us to scale efficiently to large datasets and complex behaviours by being run-time independent of dataset extent during deployment. We demonstrate the scalability and the performance of the proposed approach on an ambitious dataset collected over the course of one year including more than 25k demonstration trajectories extracted from over 120km of driving around pedestrianised areas in the city of Milton Keynes, UK. We evaluate the resulting cost representations by showing the advantages over a carefully manually designed cost map and, in addition, demonstrate its robustness to systematic errors by learning precise cost-maps even in the presence of system calibration perturbations.
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paper_title: Road Traversability analysis using network properties of roadmaps

paper_content:

Traversability analysis is an important aspect of autonomous navigation in robotics. In this paper, we relate the idea of traversability to safety and ease of road usage by defining a novel sensor-data driven metric called Road Traversability Index (RTI). The RTI translate the geometric interaction of vehicle with road into a distance modulated index that can be used as advice for a human driver or an autonomous agent intending to traverse a particular road segment using a specific vehicle. We present a framework in which 3D sensor data is converted into a road model, which in turn is converted into a roadmap based motion planning graph to represent the underlying configuration space. The RTI is defined as a function of the roadmap by axiomatically satisfying all required properties of road traversability. We have tested our algorithmic framework on simulated scenarios to explore safety; and real-world data sets to discover aspects of traversability for vehicles of various types. Experimental results show that RTI is a practical tool that reveals information that may be hidden to human inspection or other methods of assessment that do not explicitly model a vehicle.
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paper_title: Field trial of an information-providing robot in a shopping mall

paper_content:

We developed an information-providing robot for a shopping mall. It moves around and hands over flyers about the mall and when people are interested or approach the robot to obtain some information, it starts the information-providing service. During the information-providing service, it provides directions and recommendations of shops in the mall. The robot is developed to be fully autonomous, but due to low performance in automatic speech recognition, this function is overtaken by a human operator. In our field trial, the robot worked for 53.4 hours (over 11 days) without any major failure (83.5% of time autonomously operated). We conducted interviews with visitors, and revealed that the majority of them found the information from the robot useful, and wanted to use it again.
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paper_title: ReFrESH: A self-adaptation framework to support fault tolerance in field mobile robots

paper_content:

Mobile robots are being employed far more often in extreme environments, such as urban search and rescue, with greater levels of autonomy; yet recent studies on field robotics show that numerous failure modes affect the reliability of the robot in meeting mission objectives. Therefore, fault tolerance is increasingly important for field robots operating in unpredictable environments to ensure safety and effectiveness of the system. This paper demonstrates a self-adaptation frame- work, ReFrESH, that contains mechanisms for fault detection and fault mitigation. The goal of ReFrESH is to provide diagnosable and maintainable infrastructure support, built into a real-time operating system, to manage task performance in the presence of unexpected uncertainties. ReFrESH augments the port-based object framework by attaching evaluation and estimation mechanisms to each functional component so that the robot can easily detect and locate faults. In conjunction, a task level decision mechanism interacts with the fault detection elements in order to generate and choose an optimal approach to mitigating faults. Moreover, to increase flexibility of the fault tolerance, ReFrESH provides self-adaptation support for both software and hardware functionality. To our knowledge, this is the first framework to support both software and hardware self- adaptation. A demonstrative application of ReFrESH illustrates its applicability through a target tracking task deployed on a mobile robot system.
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paper_title: Proactively Approaching Pedestrians with an Autonomous Mobile Robot in Urban Environments

paper_content:

This paper presents a trajectory planning method enabling autonomous robots to approach people in dynamic environments to initiate a conversation proactively. It is shown how integrating human inspired parameters in optimal control based motion planning enables people to predict and read the purpose of a motion more easily.
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paper_title: Map-optimized probabilistic traffic rule evaluation

paper_content:

Current traffic rule handling in autonomous driving relies on non-scalable methods such as explicitly hard-coding sets of logical statements to evaluate rules. This is sufficient for early prototypes but is not scalable for larger systems designed to work in arbitrary locations. Such methods can also become problematic when traversing different geographical entities with changing traffic rules. Additionally, they do not adequately convey the uncertainty of the traffic rule evaluation stemming from uncertainty in sensor measurements. We propose an exchangeable traffic rules module which takes a knowledge base of sentences in first-order logic as input. These sentences consist of a limited number of high-level queries which are independent of local jurisdiction (e.g. can I turn right?). The knowledge base is then compiled into a potentially large logic graph. However, only a relatively small subset of the knowledge base is relevant for specific road geometries (e.g. some of the rules applicable to an intersection is not relevant for a T-junction). Since detailed road maps are available for autonomous driving, this information can be used to resolve these subsets in the knowledge base which only require map knowledge. Therefore, map information can be used to convert a single, large logic graph into a set of smaller, map-optimized logic graphs pruned for specific road geometries. The optimized graphs are then converted into Bayesian networks to facilitate probabilistic inference. Experiments were conducted using a traffic and scenario simulation framework. The results demonstrate a significant improvement in performance when using map-optimized logic graphs over a traditional first-order logic knowledge base.
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paper_title: Robots asking for directions: the willingness of passers-by to support robots

paper_content:

This paper reports about a human-robot interaction field trial conducted with the autonomous mobile robot ACE (Autonomous City Explorer) in a public place, where the ACE robot needs the support of human passers-by to find its way to a target location. Since the robot does not possess any prior map knowledge or GPS support, it has to acquire missing information through interaction with humans. The robot thus has to initiate communication by asking for the way, and retrieves information from passers-by showing the way by gestures (pointing) and marking goal positions on a still image on the touch screen of the robot. The aims of the field trial where threefold: (1) Investigating the aptitude of the navigation architecture, (2) Evaluating the intuitiveness of the interaction concept for the passers-by, (3) Assessing people's willingness to support the ACE robot in its task, i.e. assessing the social acceptability. The field trial demonstrates that the architecture enables successful autonomous path finding without any prior map knowledge just by route directions given by passers-by. An additional street survey and observational data moreover attests the intuitiveness of the interaction paradigm and the high acceptability of the ACE robot in the public place.
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paper_title: iCharibot: Design and Field Trials of a Fundraising Robot

paper_content:

In this work, we address the problem of increasing charitable donations through a novel, engaging fundraising robot: the Imperial Charity Robot (iCharibot). To better understand how to engage passers-by, we conducted a field trial in outdoor locations at a busy area in London, spread across 9 sessions of 40 minutes each. During our experiments, iCharibot attracted 679 people and engaged with 386 individuals. Our results show that interactivity led to longer user engagement with the robot. Our data further suggests both saliency and interactivity led to an increase in the total donation amount. These findings should prove useful for future design of robotic fundraisers in particular and for social robots in general.
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paper_title: Minotaurus: A System for Affective Human–Robot Interaction in Smart Environments

paper_content:

A service robot should be able to detect and identify the user in order to personalize its services and guarantee security, it should recognize the user’s emotions to allow affective interaction, and it should be able to communicate easily with the user and understand given commands by recognizing speech and gestures. Our research is motivated, for example, by the emerging needs of elderly care, health care, safety, and logistics. We have developed a distributed system for affective human–robot interaction which combines all the basic sensory elements and can collaborate with a smart environment and obtain further knowledge from the Internet. The realized HRI robot, Minotaurus, runs in real time and is capable of interacting with human beings. Minotaurus forms a rather generic platform for experimenting with human–robot collaboration in different applications and environments.
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paper_title: The effect of robot appearance types on motivating donation

paper_content:

According to the Hawthorne effect, when people feel someone staring at them, they tend to be moral because of psychological pressure. We applied this Hawthorne effect to the appearance design of robots and examined the effect of robot appearance types on motivating donation. We executed a 2 (appearance types: anthropomorphic vs. functional) within-participants experiment (N=20). Participants perceived more social presence to an anthropomorphic robot than a functional robot. In addition, participants were more willing to donate when interacting with an anthropomorphic robot than a functional robot. Categories and Subject Descriptors I.2.9 [Artificial Intelligence]: Robotics – commercial robots and applications; H.5.2 [Information Interfaces and Presentation]: User Interfaces – user-centered design
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paper_title: Autonomous robotic monitoring of underground cable systems

paper_content:

Maintenance of distributed infrastructures requires periodic measurement of many physical variables at numerous locations. This task can potentially be accomplished with autonomous robotic mobile platforms. The challenges in realizing this vision include electromechanical design of the robot itself, integration of sensors able to estimate the physical properties of the infrastructure, and autonomous operation. This paper describes the electromechanical and sensing system design of the autonomous robot for the inspection of electric power cables. The multiprocessor distributed control architecture developed in this project allows real-time operation of multiple sensors and a possibility to switch between an autonomous mode of operation and a remote-controlled one. The diagnostic sensor array includes thermal, visual, dielectric, and acoustic sensors for the measurement of cable status. Laboratory tests demonstrate the ability of integrated sensors to measure parameters of interest with the resolution required by the application. Field tests in the underground cable system demonstrate the ability of the designed platform to travel along the cable, navigate typical obstacles, and communicate with the host computer
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paper_title: Humanoid robots rescuing humans and extinguishing fires for Cooperative Fire Security System using HARMS

paper_content:

Fires cause billions of dollars in damage and thousands of deaths each year. Firefighting robots are being deployed around the world to reduce the loss of human life and the amount of property damage. High-rise buildings are used for both business and family homes. Buildings with dozens of floors present a great challenge to firefighters. Firefighter ladders cannot reach high enough to fight fires at the top of the building. Going into the building itself, in order to extinguish the blazing fire, is typically too dangerous and puts firefighters at risk. Monitoring, locating, and extinguishing the fire in the smallest amount of time is crucial to controlling fires in highrise buildings. This paper introduces humanoid robots capable of moving towards and extinguishing a fire and locating and rescuing any humans unlucky enough to be trapped in the inferno. This paper is one part of a Cooperative Fire Security System using HARMS (CFS2H) that detects, locates, and extinguishes a fire and rescues human beings using the Human, Agent, Robot, Machine, Sensor (HARMS) protocol.
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paper_title: Simulation and control of an autonomous bucket excavator for landscaping tasks

paper_content:

Introducing autonomous machines to construction areas can improve many of the occurring processes. Therefore, this paper deals with problems in the field of creating an autonomous bucket excavator. A novel behavior-based approach for motion control is presented which allows natural boom trajectories, achieves good environment disturbance compensation behavior, guarantees safety of the movements concerning human beings and structures, and keeps a high extensibility of the system for future improvements. Furthermore, a simulation of soil deals as the basis for safe tests of the excavator's behavior in a simulated dynamic environment.
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paper_title: Intelligent cooperative control for urban tracking with Unmanned Air Vehicles

paper_content:

We introduce an intelligent cooperative control system for ground target tracking in a cluttered urban environment with a team of Unmanned Air Vehicles (UAVs). We extend the work of Yu et. al. [1] to add a machine learning component that uses observations of target position to learn a model of target motion. Our learner is the Sequence Memoizer [2], a Bayesian model for discrete sequence data, which we use to predict future target location identifiers, given a context of previous location identifiers. Simulated cooperative control of a team of 3 UAVs in a 100-block city filled with various sizes of buildings verifies that learning a model of target motion can improve target tracking performance.
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paper_title: Concept and Design of A Fully Autonomous Sewer Pipe Inspection Mobile Robot "KANTARO"

paper_content:

In current conventional method, the sewer pipe inspection is undertaken using a cable-tethered robot with an on-board video camera system, completely, tele-operated by human operator. All commercial sewer inspection robots have platforms with poor mobility functions so that those robots are only capable to move into the straight pipes. Inspecting the sewage pipes using the state of the arts inspection methods by the current robots is costly, mostly human cost, and not fast enough to check and inspect the amount of sewage pipes will grow stronger than it has actually happened, specially in Japan. In order to realize inexpensive and effective inspection system, an autonomous pipe inspection method should be introduced to improve the inspection efficiency by reducing the time and manpower in the inspection process. The development of a fully autonomous pipe inspection system, requires design and development of an un-tethered mobile robot equipped with the required sensors using for autonomous pipe assessment and damage detection, and capability of navigating, completely, autonomously inside of sewer networks including different types of pipe-bends such as curves and junctions. KANTARO, presented in this paper, is the prototype of a passive-active intelligent, fully autonomous, un-tethered robot which has an intelligent modular architecture in its sensor and mechanism. KANTARO prototype robot, including a novel passive-active intelligent moving mechanism, can move into the straight pipe and pass various kinds of pipe bends without need to any intelligence of the controller or sensor reading. In order to realize a fully autonomous inspection robot, we also developed a small and intelligent 2D laser scanner for detecting of the navigational landmarks, independently with the main computer system, and fusion with a fish eye camera to assess the pipe state and fault detection.
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paper_title: Visual industrial inspection using aerial robots

paper_content:

The use of unmanned aerial vehicles (UAV) offers a unique possibility to capture visual information in areas which are hard to reach or dangerous for humans. For UAVs to become a standard tool in visual inspection, it is of utmost importance that the aerial robot can be operated efficiently by a non-expert UAV pilot and that the navigation system is robust enough to remain operational in rough, industrial conditions. To this end, we present a UAV navigation system setup that uses visual-inertial sensor cues to estimate the UAV pose as well as to create a dense 3D map of the environment in real-time onboard the UAV, completely independent of GPS. The proposed navigation system enables the operator to directly interface the UAV using high-level commands such as waypoints or velocity commands while the navigation system ensures a stable and collision-free flight.
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paper_title: Leveraging Open Data for Supporting a Cloud Robotics Service in a Smart City Environment

paper_content:

At the dawn of cloud robotics , one of the biggest challenges is to successfully exploit the power offered by the internet for acquiring and sharing information, in order to build a common knowledge base among the agents. In this paper , we propose a cloud robotics service for emergency management in a smart city scenario. The application is capable of collecting significant open data over the internet. Then it uses them in the mission planning phase, in order to autonomously define a set of waypoints toward the target coordinates.
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paper_title: Energy optimal control to approach traffic lights

paper_content:

In this paper energy optimal solutions for the approach of red traffic lights are derived. As cars waste most of the fuel in city traffic and especially in queuing at traffic lights, the presented framework provides solutions to save fuel and to protect the environment. The solutions are obtained using the definition of spent physical work which has to be minimized. It covers both cases, that the time of switching of the traffic lights is known and that the time of switching can only be modeled as a stochastic process. For a known time of switching a continuous solution is derived using Pontryagin Minimum Principle; in the stochastic case a modified Bellmann equation is formulated. The latter is solved with dynamic programming techniques. The presented solutions can be used for autonomous driving as well as for driving assistant systems. Simulation results show the potential savings using the presented approach.
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paper_title: Cloud-Enhanced Robotic System for Smart City Crowd Control

paper_content:

Cloud robotics in smart cities is an emerging paradigm that enables autonomous robotic agents to communicate and collaborate with a cloud computing infrastructure. It complements the Internet of Things (IoT) by creating an expanded network where robots offload data-intensive computation to the ubiquitous cloud to ensure quality of service (QoS). However, offloading for robots is significantly complex due to their unique characteristics of mobility, skill-learning, data collection, and decision-making capabilities. In this paper, a generic cloud robotics framework is proposed to realize smart city vision while taking into consideration its various complexities. Specifically, we present an integrated framework for a crowd control system where cloud-enhanced robots are deployed to perform necessary tasks. The task offloading is formulated as a constrained optimization problem capable of handling any task flow that can be characterized by a Direct Acyclic Graph (DAG). We consider two scenarios of minimizing energy and time, respectively, and develop a genetic algorithm (GA)-based approach to identify the optimal task offloading decisions. The performance comparison with two benchmarks shows that our GA scheme achieves desired energy and time performance. We also show the adaptability of our algorithm by varying the values for bandwidth and movement. The results suggest their impact on offloading. Finally, we present a multi-task flow optimal path sequence problem that highlights how the robot can plan its task completion via movements that expend the minimum energy. This integrates path planning with offloading for robotics. To the best of our knowledge, this is the first attempt to evaluate cloud-based task offloading for a smart city crowd control system.
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paper_title: An Informationally Structured Room for Robotic Assistance †

paper_content:

The application of assistive technologies for elderly people is one of the most promising and interesting scenarios for intelligent technologies in the present and near future. Moreover, the improvement of the quality of life for the elderly is one of the first priorities in modern countries and societies. In this work, we present an informationally structured room that is aimed at supporting the daily life activities of elderly people. This room integrates different sensor modalities in a natural and non-invasive way inside the environment. The information gathered by the sensors is processed and sent to a centralized management system, which makes it available to a service robot assisting the people. One important restriction of our intelligent room is reducing as much as possible any interference with daily activities. Finally, this paper presents several experiments and situations using our intelligent environment in cooperation with our service robot.
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paper_title: A Cloud Robotics Solution to Improve Social Assistive Robots for Active and Healthy Aging

paper_content:

Technological innovation in robotics and ICT represents an effective solution to tackle the challenge of providing social sustainable care services for the ageing population. The recent introduction of cloud technologies is opening new opportunities for the provisioning of advanced robotic services based on the cooperation of a number of connected robots, smart environments and devices improved by the huge cloud computational and storage capability. In this context, this paper aims to investigate and assess the potentialities of a cloud robotic system for the provisioning of assistive services for the promotion of active and healthy ageing. The system comprised two different smart environments, located in Italy and Sweden, where a service robot is connected to a cloud platform for the provisioning of localization based services to the users. The cloud robotic services were tested in the two realistic environments to assess the general feasibility of the solution and demonstrate the ability to provide assistive location based services in a multiple environment framework. The results confirmed the validity of the solution but also suggested a deeper investigation on the dependability of the communication technologies adopted in such kind of systems.
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paper_title: Sliding Autonomy in Cloud Robotics Services for Smart City Applications

paper_content:

The aim of this paper is to present a sliding autonomy approach for Unmanned Aerial Vehicles (UAVs) in the context of the project Fly4SmartCity. The project consists in the implementation of a cloud robotics service in which small UAVs are employed for emergency management, monitoring and surveillance in a smart city scenario. Human-robot interaction is mediated by the cloud robotics platform. We imagine three main levels of autonomy for UAVs: full autonomy, mixed-initiative and teleoperation. Then we propose different scenarios in which we analyze the Level Of Autonomy and the sliding autonomy approach. All services use shared knowledge (crowdsourcing and other data sources available on the Internet) for the management and control of the UAVs.
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paper_title: The Presentation of Self in Everyday Life

paper_content:

hen an individual enters the presence of oth ers, they commonly seek to acquire information about him or to bring into play information about him already possessed. They will be interested in his general socio-economic status, his concep tion of self, his attitude toward them, his compe tence, his trustworthiness, etc. Although some of this information seems to be sought almost as an end in itself, there are usually quite practical reasons for acquiring it. Information about the individual helps to define the situation, enabling others to know in advance what he will expect of them and what they may expect of him. Informed in these ways, the others will know how best to act in order to call forth a desired response from him. For those present, many sources of information become accessible and many carriers (or “signvehicles”) become available for conveying this information. If unacquainted with the individual, observers can glean clues from his conduct and appearance which allow them to apply their previ ous experience with individuals roughly similar to the one before them or, more important, to apply untested stereotypes to him. They can also assume from past experience that only individuals of a par ticular kind are likely to be found in a given social setting. They can rely on what the individual says about himself or on documentary evidence he provides as to who and what he is. If they know, or know of, the individual by virtue of experience prior to the interaction, they can rely on assumptions as to the persistence and generality of psychological traits as a means of predicting his present and future behavior. However, during the period in which the indi vidual is in the immediate presence of the others, few events may occur which directly provide the others with the conclusive information they will need if they are to direct wisely their own activity . Many crucial facts lie beyond the time and place of interaction or lie concealed within it. For example, the “true” or “real” attitudes, beliefs, and emotions of the individual can be ascertained only indirectly , through his avowals or through what appears to be involuntary expressive behavior. Similarly , if the individual offers the others a product or service, they will often find that during the interaction there will be no time and place immediately available for eating the pudding that the proof can be found in. They will be forced to accept some events as con ventional or natural signs of something not directly available to the senses. In Ichheiser ’s terms, 1 the individual will have to act so that he intentionally or unintentionally expresses himself, and the others will in turn have to be impressed in some way by him.…
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paper_title: Addressing exploitability of Smart City data

paper_content:

Central to a number of emerging Smart Cities are online platforms for data sharing and reuse: Data Hubs and Data Catalogues. These systems support the use of data by developers through enabling data discoverability and access. As such, the effectiveness of a Data Catalogue can be seen as the way in which it supports ‘data exploitability’: the ability to assess whether the provided data is appropriate to the given task. Beyond technical compatibility, this also regards validating the policies attached to data. Here, we present a methodology to enable Smart City Data Hubs to better address exploitability by considering the way policies propagate across the data flows applied in the system.
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paper_title: A data lifeCycle model for smart cities

paper_content:

Smart Cities are the most challenging and promising technological solutions for absorbing the increasing pressure of population growth, while simultaneously enforcing a sustainable economic progress as well as a higher quality of life. Several technologies are involved in a potential Smart City deployment, although data are the fuel to achieve the demanded and mandatory smartness. Data can be obtained from multiple sources, in large quantities, and with a variety of formats, therefore, an appropriate management is critical for their effective usage. Data life cycle models constitute an effective trend towards developing an integral and efficient data management framework, from data creation to data consumption and removal. In this paper we present the Smart City Comprehensive Data LifeCycle (SCC-DLC) model, a data management architecture generated from a comprehensive scenario agnostic model, tailored for the particular scenario of Smart Cities. We define the management of each data life phase, and describe its implementation on a Smart City with Fog-to-Cloud (F2C) resources management, an architecture that combines the advantages of both cloud and fog strategies.
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paper_title: A Cloud Based Service for Management and Planning of Autonomous UAV Missions in Smart City Scenarios

paper_content:

Cloud Robotics is an emerging paradigm in which robots, seen as abstract agents, have the possibility to connect to a common network and share on a complex infrastructure the information and knowledge they gather about the physical world; or conversely consume the data collected by other agents or made available on accessible database and repositories. In this paper we propose an implementation of an emergency-management service exploiting the possibilities offered by cloud robotics in a smart city scenario. A high-level cloud-platform manages a number of unmanned aerial vehicles (quadrotor UAVs) with the goal of providing aerial support to citizens that require it via a dedicated mobile app. The UAV reaches the citizen while forwarding a real-time video streaming to a privileged user (police officer),connected to the same cloud platform, that is allowed to teleoperate it by remote.
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paper_title: Humanoid robots rescuing humans and extinguishing fires for Cooperative Fire Security System using HARMS

paper_content:

Fires cause billions of dollars in damage and thousands of deaths each year. Firefighting robots are being deployed around the world to reduce the loss of human life and the amount of property damage. High-rise buildings are used for both business and family homes. Buildings with dozens of floors present a great challenge to firefighters. Firefighter ladders cannot reach high enough to fight fires at the top of the building. Going into the building itself, in order to extinguish the blazing fire, is typically too dangerous and puts firefighters at risk. Monitoring, locating, and extinguishing the fire in the smallest amount of time is crucial to controlling fires in highrise buildings. This paper introduces humanoid robots capable of moving towards and extinguishing a fire and locating and rescuing any humans unlucky enough to be trapped in the inferno. This paper is one part of a Cooperative Fire Security System using HARMS (CFS2H) that detects, locates, and extinguishes a fire and rescues human beings using the Human, Agent, Robot, Machine, Sensor (HARMS) protocol.
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paper_title: Addressing exploitability of Smart City data

paper_content:

Central to a number of emerging Smart Cities are online platforms for data sharing and reuse: Data Hubs and Data Catalogues. These systems support the use of data by developers through enabling data discoverability and access. As such, the effectiveness of a Data Catalogue can be seen as the way in which it supports ‘data exploitability’: the ability to assess whether the provided data is appropriate to the given task. Beyond technical compatibility, this also regards validating the policies attached to data. Here, we present a methodology to enable Smart City Data Hubs to better address exploitability by considering the way policies propagate across the data flows applied in the system.
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paper_title: The STRANDS Project: Long-Term Autonomy in Everyday Environments

paper_content:

Thanks to the efforts of the robotics and autonomous systems community, the myriad applications and capacities of robots are ever increasing. There is increasing demand from end users for autonomous service robots that can operate in real environments for extended periods. In the Spatiotemporal Representations and Activities for Cognitive Control in Long-Term Scenarios (STRANDS) project (http://strandsproject.eu), we are tackling this demand head-on by integrating state-of-the-art artificial intelligence and robotics research into mobile service robots and deploying these systems for long-term installations in security and care environments. Our robots have been operational for a combined duration of 104 days over four deployments, autonomously performing end-user-defined tasks and traversing 116 km in the process. In this article, we describe the approach we used to enable long-term autonomous operation in everyday environments and how our robots are able to use their long run times to improve their own performance.
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paper_title: Minotaurus: A System for Affective Human–Robot Interaction in Smart Environments

paper_content:

A service robot should be able to detect and identify the user in order to personalize its services and guarantee security, it should recognize the user’s emotions to allow affective interaction, and it should be able to communicate easily with the user and understand given commands by recognizing speech and gestures. Our research is motivated, for example, by the emerging needs of elderly care, health care, safety, and logistics. We have developed a distributed system for affective human–robot interaction which combines all the basic sensory elements and can collaborate with a smart environment and obtain further knowledge from the Internet. The realized HRI robot, Minotaurus, runs in real time and is capable of interacting with human beings. Minotaurus forms a rather generic platform for experimenting with human–robot collaboration in different applications and environments.
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paper_title: Human-Friendly Networked Partner Robots toward Sophisticated Services for A Community

paper_content:

This paper discusses the role of partner robots networked in SICE City. In order to realize sophisticated services for a community, the city design based on ubiquitous sensor network is very important. If a public office can be a service provider, service engineering can easily gather opinions of a resident as a user. A robot can be used as an interface connecting the physical world with the cyber world and as a human-friendly life-support system. Furthermore, the structurization of available environmental information is very important for robots interacting with humans. Robots can receive environmental information through the network from the environmental system. In this paper, we show several experimental results on the networked partner robots interacting with humans.
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paper_title: An Informationally Structured Room for Robotic Assistance †

paper_content:

The application of assistive technologies for elderly people is one of the most promising and interesting scenarios for intelligent technologies in the present and near future. Moreover, the improvement of the quality of life for the elderly is one of the first priorities in modern countries and societies. In this work, we present an informationally structured room that is aimed at supporting the daily life activities of elderly people. This room integrates different sensor modalities in a natural and non-invasive way inside the environment. The information gathered by the sensors is processed and sent to a centralized management system, which makes it available to a service robot assisting the people. One important restriction of our intelligent room is reducing as much as possible any interference with daily activities. Finally, this paper presents several experiments and situations using our intelligent environment in cooperation with our service robot.
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paper_title: A Cloud Robotics Solution to Improve Social Assistive Robots for Active and Healthy Aging

paper_content:

Technological innovation in robotics and ICT represents an effective solution to tackle the challenge of providing social sustainable care services for the ageing population. The recent introduction of cloud technologies is opening new opportunities for the provisioning of advanced robotic services based on the cooperation of a number of connected robots, smart environments and devices improved by the huge cloud computational and storage capability. In this context, this paper aims to investigate and assess the potentialities of a cloud robotic system for the provisioning of assistive services for the promotion of active and healthy ageing. The system comprised two different smart environments, located in Italy and Sweden, where a service robot is connected to a cloud platform for the provisioning of localization based services to the users. The cloud robotic services were tested in the two realistic environments to assess the general feasibility of the solution and demonstrate the ability to provide assistive location based services in a multiple environment framework. The results confirmed the validity of the solution but also suggested a deeper investigation on the dependability of the communication technologies adopted in such kind of systems.
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paper_title: Adaptive patrolling by mobile robot for changing visitor trends

paper_content:

In this paper, a single mobile robot is used to patrol an indoor environment composed of rooms. The robot is required to monitor the rooms and detect visitors as many as possible. A key idea in the patrolling mission is to allow the robot to utilize information about visitor trends. Thus far, we have focused on a visiting probability as the trend. However, the visitor trends usually change over time. Therefore, the robot is further required to detect the changes and identify the correct visitor trends in each room. For this challenge, we present a novel change-point detection method. In this method, the Jensen-Shannon divergence is used as a dissimilarity measure between two distributions of the visiting probability. The change-point detection method is activated in the Bayesian learning for estimating the changed visiting probability. Consequently, the robot is allowed to adaptively patrol the changing environment. Through the simulation experiments, we discuss the effectiveness of the adaptive patrolling for the changes in the visitor trends.
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paper_title: Do you remember that shop?: computational model of spatial memory for shopping companion robots

paper_content:

We aim to develop a shopping companion robot that can share experience with users. In this study, we focused on the shared memory acquired when a robot walks together with a user. We developed a computational model of memory recall of visited locations in a shopping mall. The model was developed with data collection from 30 participants. We found that shop size, color intensity of facade, relative visibility, and time elapsed are the influencing features for recall. The model was used in a scenario of a shopping companion robot. The robot, Robovie, autonomously follows a user while inferring the user's memory recall of shops in the visited route. When the user asks the location of other shops, Robovie replied with destination description, referring to the known locations inferred with the model of the user's memory recall. With this scenario, we verified the effectiveness of the developed computational model of memory recall. The evaluation experiment revealed that the model outputs shops that the participants are likely to recall, and makes the directions given easier to understand.
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paper_title: A Communication Robot in a Shopping Mall

paper_content:

This paper reports our development of a communication robot for use in a shopping mall to provide shopping information, offer route guidance, and build rapport. In the development, the major difficulties included sensing human behaviors, conversation in a noisy daily environment, and the needs of unexpected miscellaneous knowledge in the conversation. We chose a network-robot system approach, where a single robot's poor sensing capability and knowledge are supplemented by ubiquitous sensors and a human operator. The developed robot system detects a person with floor sensors to initiate interaction, identifies individuals with radio-frequency identification (RFID) tags, gives shopping information while chatting, and provides route guidance with deictic gestures. The robot was partially teleoperated to avoid the difficulty of speech recognition as well as to furnish a new kind of knowledge that only humans can flexibly provide. The information supplied by a human operator was later used to increase the robot's autonomy. For 25 days in a shopping mall, we conducted a field trial and gathered 2642 interactions. A total of 235 participants signed up to use RFID tags and, later, provided questionnaire responses. The questionnaire results are promising in terms of the visitors' perceived acceptability as well as the encouragement of their shopping activities. The results of the teleoperation analysis revealed that the amount of teleoperation gradually decreased, which is also promising.
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paper_title: Neel: an intelligent shopping guide - using web data for rich interactions

paper_content:

The project Myneel and its portal myneel.com together were envisaged to provide us with crucial insights into the commercialization of service robots. In this paper we describe our system and propose an approach to develop an interactive conversational agent which can serve shopping needs of the visitors in a shopping mall.
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paper_title: Human-Robot Interaction in Public and Smart Spaces

paper_content:

We have developed a “network robot system” framework with the objective of enabling practical deployment of social robots to provide real-world services in everyday social environments. This framework addresses practical issues in social human-robot interaction by integrating ambient intelligence systems, networked data stores, human supervisors, and centralized planning. All of the elements of the system have been developed and tested in public and commercial spaces such as shopping malls, resulting in a flexible robot control architecture based on practical, real-world requirements. We describe several elements of the system and demonstrate examples of its use in five years of real-world field deployments and research. Finally, we present the Ubiquitous Network Robot Platform (UNR-PF), an internationally-standardized high-level architecture for service robots based on our framework.
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paper_title: The MuMMER project: Engaging human-robot interaction in real-world public spaces

paper_content:

MuMMER (MultiModal Mall Entertainment Robot) is a four-year, EU-funded project with the overall goal of developing a humanoid robot (SoftBank Robotics’ Pepper robot being the primary robot platform) with the social intelligence to interact autonomously and naturally in the dynamic environments of a public shopping mall, providing an engaging and entertaining experience to the general public. Using co-design methods, we will work together with stakeholders including customers, retailers, and business managers to develop truly engaging robot behaviours. Crucially, our robot will exhibit behaviour that is socially appropriate and engaging by combining speech-based interaction with non-verbal communication and human-aware navigation. To support this behaviour, we will develop and integrate new methods from audiovisual scene processing, social-signal processing, high-level action selection, and human-aware robot navigation. Throughout the project, the robot will be regularly deployed in Ideapark, a large public shopping mall in Finland. This position paper describes the MuMMER project: its needs, the objectives, R&D challenges and our approach. It will serve as reference for the robotics community and stakeholders about this ambitious project, demonstrating how a co-design approach can address some of the barriers and help in building follow-up projects.
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paper_title: Field Trial of a Networked Robot at a Train Station

paper_content:

We developed a networked robot system in which ubiquitous sensors support robot sensing and a human operator processes the robot’s decisions during interaction. To achieve semi-autonomous operation for a communication robot functioning in real environments, we developed an operator-requesting mechanism that enables the robot to detect situations that it cannot handle autonomously. Therefore, a human operator helps by assuming control with minimum effort. The robot system consists of a humanoid robot, floor sensors, cameras, and a sound-level meter. For helping people in real environments, we implemented such basic communicative behaviors as greetings and route guidance in the robot and conducted a field trial at a train station to investigate the robot system’s effectiveness. The results attest to the high acceptability of the robot system in a public space and also show that the operator-requesting mechanism correctly requested help in 84.7% of the necessary situations; the operator only had to control 25% of the experiment time in the semi-autonomous mode with a robot system that successfully guided 68% of the visitors.
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paper_title: Field trial of an information-providing robot in a shopping mall

paper_content:

We developed an information-providing robot for a shopping mall. It moves around and hands over flyers about the mall and when people are interested or approach the robot to obtain some information, it starts the information-providing service. During the information-providing service, it provides directions and recommendations of shops in the mall. The robot is developed to be fully autonomous, but due to low performance in automatic speech recognition, this function is overtaken by a human operator. In our field trial, the robot worked for 53.4 hours (over 11 days) without any major failure (83.5% of time autonomously operated). We conducted interviews with visitors, and revealed that the majority of them found the information from the robot useful, and wanted to use it again.
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paper_title: Proactively Approaching Pedestrians with an Autonomous Mobile Robot in Urban Environments

paper_content:

This paper presents a trajectory planning method enabling autonomous robots to approach people in dynamic environments to initiate a conversation proactively. It is shown how integrating human inspired parameters in optimal control based motion planning enables people to predict and read the purpose of a motion more easily.
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paper_title: Robots asking for directions: the willingness of passers-by to support robots

paper_content:

This paper reports about a human-robot interaction field trial conducted with the autonomous mobile robot ACE (Autonomous City Explorer) in a public place, where the ACE robot needs the support of human passers-by to find its way to a target location. Since the robot does not possess any prior map knowledge or GPS support, it has to acquire missing information through interaction with humans. The robot thus has to initiate communication by asking for the way, and retrieves information from passers-by showing the way by gestures (pointing) and marking goal positions on a still image on the touch screen of the robot. The aims of the field trial where threefold: (1) Investigating the aptitude of the navigation architecture, (2) Evaluating the intuitiveness of the interaction concept for the passers-by, (3) Assessing people's willingness to support the ACE robot in its task, i.e. assessing the social acceptability. The field trial demonstrates that the architecture enables successful autonomous path finding without any prior map knowledge just by route directions given by passers-by. An additional street survey and observational data moreover attests the intuitiveness of the interaction paradigm and the high acceptability of the ACE robot in the public place.
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paper_title: iCharibot: Design and Field Trials of a Fundraising Robot

paper_content:

In this work, we address the problem of increasing charitable donations through a novel, engaging fundraising robot: the Imperial Charity Robot (iCharibot). To better understand how to engage passers-by, we conducted a field trial in outdoor locations at a busy area in London, spread across 9 sessions of 40 minutes each. During our experiments, iCharibot attracted 679 people and engaged with 386 individuals. Our results show that interactivity led to longer user engagement with the robot. Our data further suggests both saliency and interactivity led to an increase in the total donation amount. These findings should prove useful for future design of robotic fundraisers in particular and for social robots in general.
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paper_title: The effect of robot appearance types on motivating donation

paper_content:

According to the Hawthorne effect, when people feel someone staring at them, they tend to be moral because of psychological pressure. We applied this Hawthorne effect to the appearance design of robots and examined the effect of robot appearance types on motivating donation. We executed a 2 (appearance types: anthropomorphic vs. functional) within-participants experiment (N=20). Participants perceived more social presence to an anthropomorphic robot than a functional robot. In addition, participants were more willing to donate when interacting with an anthropomorphic robot than a functional robot. Categories and Subject Descriptors I.2.9 [Artificial Intelligence]: Robotics – commercial robots and applications; H.5.2 [Information Interfaces and Presentation]: User Interfaces – user-centered design
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paper_title: M2M infrastructure to integrate humans, agents and robots into collectives

paper_content:

Organizations are pervasive in all aspects of human society. Most large-scale goals are carried out through the cooperation of a group of humans typically working with technologies such as robots and machines. The main goal of this research is the creation of a model and architecture to support networking, communication, interaction, organization and collective intelligence features between machines, robots, software agents, and humans. The model will allow each of these actors to cooperatively work together to accomplish large-scale goals. While machines, robots, software agents and humans are very different in their capabilities, embodiment and inherent behaviors, a core goal is to make them indistinguishable in terms of acting in an organization. When a robot communicates to another actor, it is not concerned with the physical makeup of that actor, only in its ability to solve a goal or execute a task. The goal of indistinguishable actors is not at the level of a Turing test, it gives the organization the flexibility to act as an open system, where the actors can come and exit as needed by the requirements of the overall goal set.
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paper_title: MINERVA: a second-generation museum tour-guide robot

paper_content:

This paper describes an interactive tour-guide robot, which was successfully exhibited in a Smithsonian museum. During its two weeks of operation, the robot interacted with thousands of people, traversing more than 44 km at speeds of up to 163 cm/sec. Our approach specifically addresses issues such as safe navigation in unmodified and dynamic environments, and short-term human-robot interaction. It uses learning pervasively at all levels of the software architecture.
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paper_title: The autonomous city explorer project: aims and system overview

paper_content:

As robots are gradually leaving highly structured factory environments and moving into human populated environments, they need to possess more complex cognitive abilities. Not only do they have to operate efficiently and safely in natural populated environments, but also be able to achieve higher levels of cooperation and interaction with humans. The autonomous city explorer (ACE) project envisions to create a robot that will autonomously navigate in an unstructured urban environment and find its way through interaction with humans. To achieve this, research results from the fields of autonomous navigation, path planning, environment modeling, and human-robot interaction are combined. In this paper a novel hardware platform is introduced, a system overview is given, the research foci of ACE are highlighted, approaches to the occurring challenges are proposed and analyzed, and finally some first results are presented.
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paper_title: HI Robot: Human intention-aware robot planning for safe and efficient navigation in crowds

paper_content:

We present an algorithmic framework for the early classification of human intentions, and use it to accurately predict future human motions when planning the path of a robot in an environment that is shared with humans. During an off-line learning phase, a classifier that can recognize when a human intends to interact with the robot is trained. At runtime, this trained classifier allows us to recognize humans who intend to interact with, or obstruct, the robot in some way. We validate our approach using both recorded and simulated data in an environment in which some humans intentionally obstruct the robot. Our classifier identifies these potential blockers, thus allowing the robot to safely and efficiently navigate the environment by minimizing the chances of being blocked.
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paper_title: The Interactive Museum Tour-Guide Robot

paper_content:

This paper describes the software architecture of an autonomous tour-guideltutor robot. This robot was recently deployed in the "Deutsches Museum Bonn," were it guided hundreds of visitors through the museum during a six-day deployment period. The robot's control software integrates low-level probabilistic reasoning with high-level problem solving embedded in first order logic. A collection of software innovations, described in this paper, enabled the robot to navigate at high speeds through dense crowds, while reliably avoiding collisions with obstacles--some of which could not even be perceived. Also described in this paper is a user interface tailored towards non-expert users, which was essential for the robot's success in the museum. Based on these experiences, this paper argues that time is ripe for the development of AI-based commercial service robots that assist people in everyday life.
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paper_title: Autonomous Robot Navigation in Highly Populated Pedestrian Zones

paper_content:

In the past, there has been a tremendous amount of progress in the area of autonomous robot navigation, and a large variety of robots have been developed that demonstrated robust navigation capabilities indoors, in nonurban outdoor environments, or on roads; relatively few approaches have focused on navigation in urban environments such as city centers. Urban areas, however, introduce numerous challenges for autonomous robots as they are rather unstructured and dynamic. In this paper, we present a navigation system for mobile robots designed to operate in crowded city environments and pedestrian zones. We describe the different components of this system, including a simultaneous localization and mapping module for dealing with huge maps of city centers, a planning component for inferring feasible paths, taking into account the traversability and type of terrain, a module for accurate localization in dynamic environments, and the means for calibrating and monitoring the platform. Our navigation system has been implemented and tested in several large-scale field tests, in which a real robot autonomously navigated over several kilometers in a complex urban environment. This also included a public demonstration, during which the robot autonomously traveled along a more than 3-km-long route through the city center of Freiburg, Germany.
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paper_title: A navigation system for robots operating in crowded urban environments

paper_content:

Over the past years, there has been a tremendous progress in the area of robot navigation. Most of the systems developed thus far, however, are restricted to indoor scenarios, non-urban outdoor environments, or road usage with cars. Urban areas introduce numerous challenges to autonomous mobile robots as they are highly complex and in addition to that dynamic. In this paper, we present a navigation system for pedestrian-like autonomous navigation with mobile robots in city environments. We describe different components including a SLAM system for dealing with huge maps of city centers, a planning approach for inferring feasible paths taking also into account the traversability and type of terrain, and a method for accurate localization in dynamic environments. The navigation system has been implemented and tested in several large-scale field tests in which the robot Obelix managed to autonomously navigate from our university campus over a 3.3 km long route to the city center of Freiburg.
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paper_title: Social Navigation - Identifying Robot Navigation Patterns in a Path Crossing Scenario

paper_content:

The work at hand addresses the question: What kind of navigation behavior do humans expect from a robot in a path crossing scenario? To this end, we developed the "Inverse Oz of Wizard" study design where participants steered a robot in a scenario in which an instructed person is crossing the robot's path. We investigated two aspects of robot behavior: (1) what are the expected actions? and (2) can we determine the expected action by considering the spatial relationship? ::: ::: The overall navigation strategy, that was performed the most, was driving straight towards the goal and either stop when the person and the robot came close or drive on towards the goal and pass the path of the person. Furthermore, we found that the spatial relationship is significantly correlated with the performed action and we can precisely predict the expected action by using a Support Vector Machine.
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paper_title: Autonomous navigation in dynamic social environments using Multi-Policy Decision Making

paper_content:

In dynamic environments crowded with people, robot motion planning becomes difficult due to the complex and tightly-coupled interactions between agents. Trajectory planning methods, supported by models of typical human behavior and personal space, often produce reasonable behavior. However, they do not account for the future closed-loop interactions of other agents with the trajectory being constructed. As a consequence, the trajectories are unable to anticipate cooperative interactions (such as a human yielding), or adverse interactions (such as the robot blocking the way). In this paper, we propose a new method for navigation amongst pedestrians in which the trajectory of the robot is not explicitly planned, but instead, a planning process selects one of a set of closed-loop behaviors whose utility can be predicted through forward simulation. In particular, we extend Multi-Policy Decision Making (MPDM) [1] to this domain using the closed-loop behaviors Go-Solo, Follow-other, and Stop. By dynamically switching between these policies, we show that we can improve the performance of the robot as measured by utility functions that reward task completion and penalize inconvenience to other agents. Our evaluation includes extensive results in simulation and real-world experiments.
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paper_title: Following route graphs in urban environments

paper_content:

In this paper, an approach is presented that allows a robot to navigate in an urban environment by following natural language route instructions. In this situation, neither maps nor GPS information are available to the robot thus it has to rely solely on the human-given route description and the observations from its sensors. An architecture for solving problems such as navigation on the sidewalk, street direction inference, and environment labeling that arise in this situation is presented. Our initial experiments indicate that the proposed methods enable a robot to safely navigate in urban environments by following abstract route descriptions and reach previously unknown points in a city.
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paper_title: Do you see the bakery? Leveraging geo-referenced texts for global localization in public maps

paper_content:

Text is one of the richest sources of information in an urban environment. Although textual information is heavily relied on by humans for a majority of the daily tasks, its usage has not been completely exploited in the field of robotics. In this work, we propose a localization approach utilizing textual features in urban environments. Starting at an unknown location, equipped with an RGB-camera and a compass, our approach uses off-the-shelf text extraction methods to identify text labels in the vicinity. We then apply a probabilistic localization approach with specific sensor models to integrate multiple observations. An extensive evaluation with real-world data gathered in different cities reveals an improvement over GPS-based localization when using our method.
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paper_title: Motion planning for autonomous vehicles in highly constrained urban environments

paper_content:

In this paper, we present a motion planning algorithm for autonomous navigation in highly constrained urban environments. Since common approaches to on-road trajectory planning turned out to be unsuitable for this task, we instead extended an A*-based planner originally designed for navigation in unstructured environments. Two novel node expansion methods were added to obtain smooth and accurate trajectories that consider the structure of the environment. The first one attempts to find a trajectory connecting the current node directly to the goal by solving a boundary value problem using numerical optimization. The second method leverages a simulated pure-pursuit controller to generate edges (i.e. short motion primitives) that guide the vehicle toward or along the global reference path. As a result, the planner is able to produce smooth paths while retaining the explorative power of A* that is needed to deal with challenging situations in urban driving (e.g., reversing in order to pass a vehicle that stopped unexpectedly). Its practical usefulness was demonstrated during extensive tests on an electric vehicle navigating a mock urban environment as well as on our own autonomous vehicle MuCAR-3.
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paper_title: Probabilistic collision state checker for crowded environments

paper_content:

For path planning algorithms of robots it is important that the robot does not reach a state of inevitable collision. In crowded environments with many humans or robots, the set of possible inevitable collision states (ICS) is often unacceptably high, such that the robot has to stop and wait in too many situations. For this reason, the concept of ICS is extended to probabilistic collision states (PCS), which estimates the collision probability for a given state. This allows to efficiently run planning algorithms through crowded environments when accepting a certain collision probability. A further novelty is that the obstacles possibly react to the robot in order to mitigate the risk of a collision. The results show a significant difference in interaction behavior. Thus, this approach is especially suited for active and non-deterministic moving obstacles in the robot workspace.
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paper_title: Biologically inspired SLAM using Wi-Fi

paper_content:

Wi-Fi is a commonly available source of localization information in urban environments but is challenging to integrate into conventional mapping architectures. Current state of the art probabilistic Wi-Fi SLAM algorithms are limited by spatial resolution and an inability to remove the accumulation of rotational error, inherent limitations of the Wi-Fi architecture. In this paper we leverage the low quality sensory requirements and coarse metric properties of RatSLAM to localize using Wi-Fi fingerprints. To further improve performance, we present a novel sensor fusion technique that integrates camera and Wi-Fi to improve localization specificity, and use compass sensor data to remove orientation drift. We evaluate the algorithms in diverse real world indoor and outdoor environments, including an office floor, university campus and a visually aliased circular building loop. The algorithms produce topologically correct maps that are superior to those produced using only a single sensor modality.
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paper_title: Robot navigation in dense human crowds: the case for cooperation

paper_content:

We consider mobile robot navigation in dense human crowds. In particular, we explore two questions. Can we design a navigation algorithm that encourages humans to cooperate with a robot? Would such cooperation improve navigation performance? We address the first question by developing a probabilistic predictive model of cooperative collision avoidance and goal-oriented behavior by extending the interacting Gaussian processes approach to include multiple goals and stochastic movement duration. We answer the second question with an extensive quantitative study of robot navigation in dense human crowds (488 runs completed), specifically testing how cooperation models effect navigation performance. We find that the “multiple goal” interacting Gaussian processes algorithm performs comparably with human teleoperators in crowd densities near 1 person/m2, while a state of the art noncooperative planner exhibits unsafe behavior more than 3 times as often as this multiple goal extension, and more than twice as often as the basic interacting Gaussian processes. Furthermore, a reactive planner based on the widely used “dynamic window” approach fails for crowd densities above 0.55 people/m2. Based on these experimental results, and previous theoretical observations, we conclude that a cooperation model is important for safe and efficient robot navigation in dense human crowds.
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paper_title: Improved GPS sensor model for mobile robots in urban terrain

paper_content:

Autonomous robot navigation in out-door scenarios gains increasing importance in various growing application areas. Whereas in non-urban domains such as deserts the problem of successful GPS-based navigation appears to be almost solved, navigation in urban domains particularly in the close vicinity of buildings is still a challenging problem. In such situations GPS accuracy significantly drops down due to multiple signal reflections with larger objects causing the so-called multipath error. In this paper we contribute a novel approach for incorporating multipath errors into the conventional GPS sensor model by analyzing environmental structures from online generated point clouds. The approach has been validated by experimental results conducted with an allterrain robot operating in scenarios requiring close-to-building navigation. Presented results show that positioning accuracy can significantly be improved within urban domains.
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paper_title: Cooperative autonomous driving: intelligent vehicles sharing city roads

paper_content:

The paper presents the Intelligent Control System Laboratory's (ICSL) Cooperative Autonomous Mobile Robot technologies and their application to intelligent vehicles for cities. The deployed decision and control algorithms made the road-scaled vehicles capable of undertaking cooperative autonomous maneuvers. Because the focus of ICSL's research is in decision and control algorithms, it is therefore reasonable to consider replacing or upgrading the sensors used with more recent road sensory concepts as produced by other research groups. While substantial progress has been made, there are still some issues that need to be addressed such as: decision and control algorithms for navigating roundabouts, real-time integration of all data, and decision-making algorithms to enable intelligent vehicles to choose the driving maneuver as they go. With continued research, it is feasible that cooperative autonomous vehicles will coexist alongside human drivers in the not-too-distant future.
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paper_title: Context-based detection of pedestrian crossing intention for autonomous driving in urban environments

paper_content:

This paper focuses on the detection of pedestrian crossing intention to improve the situation awareness for autonomous driving in urban environments. A new definition of pedestrian crossing intention is discussed, which allows self-driving vehicles to identify pedestrians, whose intended actions are relevant for the own behavior planning, at an early stage. We propose a context-based feature descriptor in combination with a SVM classifier for detecting this. The descriptor captures the movement of a pedestrian relative to the road and the spatial layout of other scene elements in a generic manner. The performance of the feature descriptor is evaluated in relation to various SVM setups. Feasibility of the approach is demonstrated with data captured on-board of a vehicle in real inner-city traffic. The evaluation of the classification results confirms, that context-based data is a promising indicator for pedestrian crossing intention and that the proposed feature descriptor is capable of representing this. It is further shown that a lack of information about the pedestrian's posture and body movement results in a delayed detection of the pedestrians changing their crossing intention when compared to a human observer.
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paper_title: Sharing the Road: Autonomous Vehicles Meet Human Drivers

paper_content:

In modern urban settings, automobile traffic and collisions lead to endless frustration as well as significant loss of life, property, and productivity. Recent advances in artificial intelligence suggest that autonomous vehicle navigation may soon be a reality. In previous work, we have demonstrated that a reservation-based approach can efficiently and safely govern interactions of multiple autonomous vehicles at intersections. Such an approach alleviates many traditional problems associated with intersections, in terms of both safety and efficiency. However, the system relies on all vehicles being equipped with the requisite technology-a restriction that would make implementing such a system in the real world extremely difficult. In this paper, we extend this system to allow for incremental deployability. The modified system is able to accommodate traditional human-operated vehicles using existing infrastructure. Furthermore, we show that as the number of autonomous vehicles on the road increases, traffic delays decrease monotonically toward the levels exhibited in our previous work. Finally, we develop a method for switching between various human-usable configurations while the system is running, in order to facilitate an even smoother transition. The work is fully implemented and tested in our custom simulator, and we present detailed experimental results attesting to its effectiveness.
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paper_title: Precise and efficient model-based vehicle tracking method using Rao-Blackwellized and scaling series particle filters

paper_content:

A precise and efficient tracking technique is essential for an intelligent vehicle to interact with the surrounding vehicles on the road. In this paper, we propose a model-based vehicle tracking method using the Rao-Blackwellized particle filter (RBPF) and scaling series particle filter (SSPF).
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paper_title: EureCar turbo: A self-driving car that can handle adverse weather conditions

paper_content:

Autonomous driving technology has made significant advances in recent years. In order for self-driving cars to become practical, they are required to operate safely and reliably even under adverse driving conditions. However, most current autonomous driving cars have only been shown to be operational under amiable weather conditions, i.e., on sunny days on dry roads. In order to enable autonomous cars to handle adverse driving conditions such as rain and wet roads, the algorithm must be able to detect roads within a tolerable margin of error using sensors such as cameras and laser scanners. In this paper, we propose a sensor fusion algorithms that is able to operate under a variety of weather conditions, including rain. Our algorithm was validated when a strong shower occurred during the 2014 Hyundai Motor Company's Autonomous Car Competition. In this paper, we present the competition results that were collected on the same course on both sunny and rainy days. Based on the comparison, we propose the future directions to improve the autonomous driving capability under adverse environmental conditions.
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paper_title: Watch this: Scalable cost-function learning for path planning in urban environments

paper_content:

In this work, we present an approach to learn cost maps for driving in complex urban environments from a very large number of demonstrations of driving behaviour by human experts. The learned cost maps are constructed directly from raw sensor measurements, bypassing the effort of manually designing cost maps as well as features. When deploying the learned cost maps, the trajectories generated not only replicate human-like driving behaviour but are also demonstrably robust against systematic errors in putative robot configuration. To achieve this we deploy a Maximum Entropy based, non-linear IRL framework which uses Fully Convolutional Neural Networks (FCNs) to represent the cost model underlying expert driving behaviour. Using a deep, parametric approach enables us to scale efficiently to large datasets and complex behaviours by being run-time independent of dataset extent during deployment. We demonstrate the scalability and the performance of the proposed approach on an ambitious dataset collected over the course of one year including more than 25k demonstration trajectories extracted from over 120km of driving around pedestrianised areas in the city of Milton Keynes, UK. We evaluate the resulting cost representations by showing the advantages over a carefully manually designed cost map and, in addition, demonstrate its robustness to systematic errors by learning precise cost-maps even in the presence of system calibration perturbations.
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paper_title: Road Traversability analysis using network properties of roadmaps

paper_content:

Traversability analysis is an important aspect of autonomous navigation in robotics. In this paper, we relate the idea of traversability to safety and ease of road usage by defining a novel sensor-data driven metric called Road Traversability Index (RTI). The RTI translate the geometric interaction of vehicle with road into a distance modulated index that can be used as advice for a human driver or an autonomous agent intending to traverse a particular road segment using a specific vehicle. We present a framework in which 3D sensor data is converted into a road model, which in turn is converted into a roadmap based motion planning graph to represent the underlying configuration space. The RTI is defined as a function of the roadmap by axiomatically satisfying all required properties of road traversability. We have tested our algorithmic framework on simulated scenarios to explore safety; and real-world data sets to discover aspects of traversability for vehicles of various types. Experimental results show that RTI is a practical tool that reveals information that may be hidden to human inspection or other methods of assessment that do not explicitly model a vehicle.
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paper_title: Map-optimized probabilistic traffic rule evaluation

paper_content:

Current traffic rule handling in autonomous driving relies on non-scalable methods such as explicitly hard-coding sets of logical statements to evaluate rules. This is sufficient for early prototypes but is not scalable for larger systems designed to work in arbitrary locations. Such methods can also become problematic when traversing different geographical entities with changing traffic rules. Additionally, they do not adequately convey the uncertainty of the traffic rule evaluation stemming from uncertainty in sensor measurements. We propose an exchangeable traffic rules module which takes a knowledge base of sentences in first-order logic as input. These sentences consist of a limited number of high-level queries which are independent of local jurisdiction (e.g. can I turn right?). The knowledge base is then compiled into a potentially large logic graph. However, only a relatively small subset of the knowledge base is relevant for specific road geometries (e.g. some of the rules applicable to an intersection is not relevant for a T-junction). Since detailed road maps are available for autonomous driving, this information can be used to resolve these subsets in the knowledge base which only require map knowledge. Therefore, map information can be used to convert a single, large logic graph into a set of smaller, map-optimized logic graphs pruned for specific road geometries. The optimized graphs are then converted into Bayesian networks to facilitate probabilistic inference. Experiments were conducted using a traffic and scenario simulation framework. The results demonstrate a significant improvement in performance when using map-optimized logic graphs over a traditional first-order logic knowledge base.
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paper_title: All-weather perception for man-portable robots using ultra-wideband radar

paper_content:

Autonomous man-portable robots have the potential to provide a wide range of new capabilities for both military and civilian applications. Previous research in autonomy for small robots has focused on vision, LIDAR, and sonar sensors. While vision and LIDAR work well in clear weather, they are seriously impaired by rain, snow, fog, and smoke. Sonar can penetrate adverse weather, but has limited range outdoors, and suffers from specular reflections indoors. For the Daredevil Project, we have investigated the use of ultra-wideband (UWB) radar to provide obstacle detection capabilities for man-portable robots. Our research shows that UWB radar can effectively penetrate adverse weather, including dense fog, and detect obstacles that would be undetectable by vision or LIDAR under the same conditions. We have developed filtering algorithms that process the raw radar returns to eliminate reflections from ground clutter and make obstacles easier to detect. We have tested this system on an iRobot PackBot equipped with both UWB radar and LIDAR, and we have demonstrated how UWB radar can be used for obstacle detection in obscured environments.
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paper_title: Dynamic obstacle avoidance approach for car-like robots in dynamic environments

paper_content:

In this paper, a new dynamic obstacle avoidance approach for nonholonomic mobile robots in dynamic environments is presented. In dynamic environments, the mobile robot is expected to encounter and safely avoid the obstacles along its way. This inevitably will delay the mobile robot in keeping to its original planned timeframe. To address this scenario, the proposed approach will ensure the mobile robot is able to gain the time lost during obstacle avoidance and reach the final point at the specified time. This approach is based on the dynamic trajectory planning scheme which utilized the replanning approach in order to avoid the obstacle. The performance of the proposed approach is tested through simulations in a simplified city-like dynamic environment.
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paper_title: Energy optimal control to approach traffic lights

paper_content:

In this paper energy optimal solutions for the approach of red traffic lights are derived. As cars waste most of the fuel in city traffic and especially in queuing at traffic lights, the presented framework provides solutions to save fuel and to protect the environment. The solutions are obtained using the definition of spent physical work which has to be minimized. It covers both cases, that the time of switching of the traffic lights is known and that the time of switching can only be modeled as a stochastic process. For a known time of switching a continuous solution is derived using Pontryagin Minimum Principle; in the stochastic case a modified Bellmann equation is formulated. The latter is solved with dynamic programming techniques. The presented solutions can be used for autonomous driving as well as for driving assistant systems. Simulation results show the potential savings using the presented approach.
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paper_title: Autonomous repositioning and localization of an in situ fabricator

paper_content:

Despite the prevalent use of robotic technologies in industrial manufacturing, their use on building construction sites is still very limited. This is mainly due to the unstructured nature of construction sites and the fact that the structures built must be larger than the machines which build them. This paper addresses these difficulties by presenting a repositioning and localization system which, using purely on-board sensing, allows a mobile robot to maintain a high degree of end-effector positioning accuracy while moving among numerous building positions during a building task. We introduce a newly developed machine, called the In situ Fabricator (IF), whose goal is to bring digital fabrication to the construction site. The capabilities of the repositioning and localization system is demonstrated through the construction of a vertical stack of bricks, in which the IF repositions itself after placing each brick. With this experiment, we demonstrate that the IF can build with sub-centimeter accuracy over long building sequences.
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paper_title: Mobile robotic fabrication on construction sites: DimRob

paper_content:

In this paper, viable applications for mobile robotic units on construction sites are explored. While identifying potential areas for in-situ fabrication in the construction sector, the intention is also to build upon innovative man-machine interaction paradigms to deal with the imprecision and tolerances often faced on construction sites. By combining the precision of the machine with the innate cognitive human skills, a simple but effective mobile fabrication system is tested for the building of algorithmically designed structures that would not be possible through conventional manual means. It is believed that this new approach to man-machine collaboration, aimed at a deeper integration of human ability with the strengths of digitally controlled machines, will result in advances in the construction sector, thus opening up new design and application fields for architects and planners.
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paper_title: Enabling intelligent energy management for robots using publicly available maps

paper_content:

Energy consumption represents one of the most basic constraints for mobile robot autonomy. We propose a new framework to predict energy consumption using information extracted from publicly available maps. This method avoids having to model internal robot configurations, which are often unavailable, while still providing invaluable predictions for both explored and unexplored trajectories. Our approach uses a heteroscedastic Gaussian Process to model the power consumption, which explicitly accounts for variance due to exogenous latent factors such as traffic and weather conditions. We evaluate our framework on 30km of data collected from a city centre environment with a mobile robot travelling on pedestrian walkways. Results across five different test routes show an average difference between predicted and measured power consumption of 3.3%, leading to an average error of 6.6% on predictions of energy consumption. The distinct advantage of our model is our ability to predict measurement variance. The variance predictions improved by 84.3% over a benchmark.
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paper_title: ReFrESH: A self-adaptation framework to support fault tolerance in field mobile robots

paper_content:

Mobile robots are being employed far more often in extreme environments, such as urban search and rescue, with greater levels of autonomy; yet recent studies on field robotics show that numerous failure modes affect the reliability of the robot in meeting mission objectives. Therefore, fault tolerance is increasingly important for field robots operating in unpredictable environments to ensure safety and effectiveness of the system. This paper demonstrates a self-adaptation frame- work, ReFrESH, that contains mechanisms for fault detection and fault mitigation. The goal of ReFrESH is to provide diagnosable and maintainable infrastructure support, built into a real-time operating system, to manage task performance in the presence of unexpected uncertainties. ReFrESH augments the port-based object framework by attaching evaluation and estimation mechanisms to each functional component so that the robot can easily detect and locate faults. In conjunction, a task level decision mechanism interacts with the fault detection elements in order to generate and choose an optimal approach to mitigating faults. Moreover, to increase flexibility of the fault tolerance, ReFrESH provides self-adaptation support for both software and hardware functionality. To our knowledge, this is the first framework to support both software and hardware self- adaptation. A demonstrative application of ReFrESH illustrates its applicability through a target tracking task deployed on a mobile robot system.
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paper_title: Landmark-based autonomous navigation in sewerage pipes

paper_content:

We describe a method for an autonomous mobile robot to navigate through a system of sewerage pipes. Landmarks signalling positions in the pipe system have to be detected and classified, where classification is allowed do be unreliable. Self localization is interpreted as a partially observable Markov decision problem and solved accordingly. The method is implemented and used on a prototype robot platform operating in a dry sewage pipe test network.
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paper_title: A roadwork scene signature based on the opponent colour model

paper_content:

The presence of roadworks greatly affects the validity of prior maps used for navigation by autonomous vehicles. This paper addresses the problem of quickly and robustly assessing the gist of traffic scenes for whether roadworks might be present. Without explicitly modelling individual roadwork indicators such as traffic cones, construction barriers or traffic signs, our method instead only exploits the engineered visual saliency of such objects. We draw inspiration from opponent colour vision in humans to formulate a novel roadwork scene signature based on an opponent spatial prior combined with gradient information. Finally, we apply our roadwork scene signature to the task of roadwork scene recognition, within a classification framework based on soft assignment vec-torization and RUSBoost. We evaluate our roadwork signature on real life data from our autonomous vehicle.
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paper_title: Autonomous robotic monitoring of underground cable systems

paper_content:

Maintenance of distributed infrastructures requires periodic measurement of many physical variables at numerous locations. This task can potentially be accomplished with autonomous robotic mobile platforms. The challenges in realizing this vision include electromechanical design of the robot itself, integration of sensors able to estimate the physical properties of the infrastructure, and autonomous operation. This paper describes the electromechanical and sensing system design of the autonomous robot for the inspection of electric power cables. The multiprocessor distributed control architecture developed in this project allows real-time operation of multiple sensors and a possibility to switch between an autonomous mode of operation and a remote-controlled one. The diagnostic sensor array includes thermal, visual, dielectric, and acoustic sensors for the measurement of cable status. Laboratory tests demonstrate the ability of integrated sensors to measure parameters of interest with the resolution required by the application. Field tests in the underground cable system demonstrate the ability of the designed platform to travel along the cable, navigate typical obstacles, and communicate with the host computer
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paper_title: Simulation and control of an autonomous bucket excavator for landscaping tasks

paper_content:

Introducing autonomous machines to construction areas can improve many of the occurring processes. Therefore, this paper deals with problems in the field of creating an autonomous bucket excavator. A novel behavior-based approach for motion control is presented which allows natural boom trajectories, achieves good environment disturbance compensation behavior, guarantees safety of the movements concerning human beings and structures, and keeps a high extensibility of the system for future improvements. Furthermore, a simulation of soil deals as the basis for safe tests of the excavator's behavior in a simulated dynamic environment.
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paper_title: Concept and Design of A Fully Autonomous Sewer Pipe Inspection Mobile Robot "KANTARO"

paper_content:

In current conventional method, the sewer pipe inspection is undertaken using a cable-tethered robot with an on-board video camera system, completely, tele-operated by human operator. All commercial sewer inspection robots have platforms with poor mobility functions so that those robots are only capable to move into the straight pipes. Inspecting the sewage pipes using the state of the arts inspection methods by the current robots is costly, mostly human cost, and not fast enough to check and inspect the amount of sewage pipes will grow stronger than it has actually happened, specially in Japan. In order to realize inexpensive and effective inspection system, an autonomous pipe inspection method should be introduced to improve the inspection efficiency by reducing the time and manpower in the inspection process. The development of a fully autonomous pipe inspection system, requires design and development of an un-tethered mobile robot equipped with the required sensors using for autonomous pipe assessment and damage detection, and capability of navigating, completely, autonomously inside of sewer networks including different types of pipe-bends such as curves and junctions. KANTARO, presented in this paper, is the prototype of a passive-active intelligent, fully autonomous, un-tethered robot which has an intelligent modular architecture in its sensor and mechanism. KANTARO prototype robot, including a novel passive-active intelligent moving mechanism, can move into the straight pipe and pass various kinds of pipe bends without need to any intelligence of the controller or sensor reading. In order to realize a fully autonomous inspection robot, we also developed a small and intelligent 2D laser scanner for detecting of the navigational landmarks, independently with the main computer system, and fusion with a fish eye camera to assess the pipe state and fault detection.
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paper_title: Autonomous robotic system for bridge deck data collection and analysis

paper_content:

Bridge deck inspection is conducted to identify bridge condition deterioration and, thus, to facilitate implementation of appropriate maintenance or rehabilitation procedures. In this paper, we report the development of a robotic system for bridge deck data collection and analysis. The robotic system accurately localizes itself and autonomously maneuvers on the bridge deck to collect visual images and conduct nondestructive evaluation (NDE) measurements. The developed robotic system can reduce the cost and time of the bridge deck data collection. Crack detection and mapping algorithm to build the deck crack maps is presented in detail. The electrical resistivity (ER), impact-echo (IE) and ultrasonic surface waves (USW) data collected by the robot are analyzed to generate the corrosion, delamination and concrete elastic modulus maps of the deck. The presented robotic system has been successfully deployed to inspect numerous bridges.
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paper_title: Visual industrial inspection using aerial robots

paper_content:

The use of unmanned aerial vehicles (UAV) offers a unique possibility to capture visual information in areas which are hard to reach or dangerous for humans. For UAVs to become a standard tool in visual inspection, it is of utmost importance that the aerial robot can be operated efficiently by a non-expert UAV pilot and that the navigation system is robust enough to remain operational in rough, industrial conditions. To this end, we present a UAV navigation system setup that uses visual-inertial sensor cues to estimate the UAV pose as well as to create a dense 3D map of the environment in real-time onboard the UAV, completely independent of GPS. The proposed navigation system enables the operator to directly interface the UAV using high-level commands such as waypoints or velocity commands while the navigation system ensures a stable and collision-free flight.
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paper_title: Searching for Smart City definition: a comprehensive proposal

paper_content:

During the latest years, smart city projects have been more and more popular and widespread all over the world. The continuous increasing of city’s population and the complexity of city management drive local governments towards the strong use of technologies to support a higher quality of urban spaces and a better offering of public services. The fascination of smart cities, able to link high technology, green environment and well-being for citizens, interests all the municipalities, independently on their dimensions, geographical area or culture. However, the concept of smart city is far from to be unambiguous. Several experiences all over the world show that cities define themselves as smart, but the meaning attributed to this word is different each time. Smart city concept has been growing from empirical experience, therefore a systemic theoretical study about this phenomenon still lacks. In this paper, the author aims to propose a comprehensive and verified definition of smart city, based on both a deep literature investigation about smart city studies and a large survey of smart city projects in the international panorama. The goal of this work is not only to provide a clear framework about this interesting and current topic, but also to support local governments and public administrations in effective smart city implementation, able to create public value and well being for citizens and environmental sustainability in the urban space.
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paper_title: Explaining data patterns using knowledge from the Web of Data

paper_content:

Knowledge Discovery (KD) is a long-tradition field aiming at developing methodologies to detect hidden patterns and regularities in large datasets, using techniques from a wide range of domains, such as statistics, machine learning, pattern recognition or data visualisation. In most real world contexts, the interpretation and explanation of the discovered patterns is left to human experts, whose work is to use their background knowledge to analyse, refine and make the patterns understandable for the intended purpose. Explaining patterns is therefore an intensive and time-consuming process, where parts of the knowledge can remain unrevealed, especially when the experts lack some of the required background knowledge. ::: ::: In this thesis, we investigate the hypothesis that such interpretation process can be facilitated by introducing background knowledge from the Web of (Linked) Data. In the last decade, many areas started publishing and sharing their domain-specific knowledge in the form of structured data, with the objective of encouraging information sharing, reuse and discovery. With a constantly increasing amount of shared and connected knowledge, we thus assume that the process of explaining patterns can become easier, faster, and more automated. ::: ::: To demonstrate this, we developed Dedalo, a framework that automatically provides explanations to patterns of data using the background knowledge extracted from the Web of Data. We studied the elements required for a piece of information to be considered an explanation, identified the best strategies to automatically find the right piece of information in the Web of Data, and designed a process able to produce explanations to a given pattern using the background knowledge autonomously collected from the Web of Data. ::: ::: The final evaluation of Dedalo involved users within an empirical study based on a real-world scenario. We demonstrated that the explanation process is complex when not being familiar with the domain of usage, but also that this can be considerably simplified when using the Web of Data as a source of background knowledge.
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paper_title: An ontology-based approach to improve the accessibility of ROS-based robotic systems

paper_content:

The focus of this work is to exploit ontologies to make robotic systems more accessible to non-expert users, therefore supporting the deployment of robot-integrated applications. Due to the increasing number of robotic platforms available for commercial use, robotic systems are nowadays being approached by users with different backgrounds, who are often more interested in the robots' high-level capabilities than their technical architecture. Without the right expertise however, using robots is restricted to the capabilities exposed by the platform provider, i.e. they can only be used as end products rather than as development platforms. Our hypothesis is that an ontological representation of the capabilities of robots could make these capabilities more accessible, reducing the complexity of robot programming and enabling non-experts to exploit these systems to a much larger extent. To demonstrate this, an ontology abstracting the capabilities exposed by the most common robotic middleware (ROS) is integrated in a system to allow non-experts to program robots of different types and capabilities without previous knowledge either of the specific robotic platform being considered, or of the intricate systems used in its implementation. Our experiments, in which non-experts users had to configure the system in order to make robots achieve different tasks, show how the efforts required for realizing basic tasks using available robotic platforms can be sensibly reduced through our approach.
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paper_title: Transparent, explainable, and accountable AI for robotics

paper_content:

To create fair and accountable AI and robotics, we need precise regulation and better methods to certify, explain, and audit inscrutable systems.
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paper_title: Urban robotics: Towards responsible innovations for our cities

paper_content:

Abstract Emerging developments in robotics technologies combined with ambient intelligent infrastructures may radically improve the quality of life in cities. Urban robotics is a research area encompassing diverse applications for the urban environment. In particular, the term is used to refer to military, search and rescue and civil applications. In this article, we take into account civil applications. The article discusses the role of social desirability and responsibility in the design of robots and proposes a method for identifying the implications deriving from the interaction between the robot and the physical and non-physical properties of the urban environment. Among the issues discussed are: the phenomenon of vandalism, the rules of urban decorum, the social resistance towards technological displacement, and finally the new “soft” risks engendered by human–robot social interactions.
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paper_title: Building Information Modeling (BIM): Trends, Benefits, Risks, and Challenges for the AEC Industry

paper_content:

Building information modeling (BIM) is one of the most promising recent developments in the architecture, engineering, and construction (AEC) industry. With BIM technology, an accurate virtual model of a building is digitally constructed. This model, known as a building information model, can be used for planning, design, construction, and operation of the facility. It helps architects, engineers, and constructors visualize what is to be built in a simulated environment to identify any potential design, construction, or operational issues. BIM represents a new paradigm within AEC, one that encourages integration of the roles of all stakeholders on a project. In this paper, current trends, benefits, possible risks, and future challenges of BIM for the AEC industry are discussed. The findings of this study provide useful information for AEC industry practitioners considering implementing BIM technology in their projects.
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paper_title: Ambient Intelligence: Technologies, Applications, and Opportunities

paper_content:

Ambient intelligence is an emerging discipline that brings intelligence to our everyday environments and makes those environments sensitive to us. Ambient intelligence (AmI) research builds upon advances in sensors and sensor networks, pervasive computing, and artificial intelligence. Because these contributing fields have experienced tremendous growth in the last few years, AmI research has strengthened and expanded. Because AmI research is maturing, the resulting technologies promise to revolutionarize daily human life by making people's surroundings flexible and adaptive. In this paper, we provide a survey of the technologies that comprise ambient intelligence and of the applications that are dramatically affected by it. In particular, we specifically focus on the research that makes AmI technologies ''intelligent''. We also highlight challenges and opportunities that AmI researchers will face in the coming years.
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paper_title: Cloud robotics: architecture, challenges and applications

paper_content:

We extend the computation and information sharing capabilities of networked robotics by proposing a cloud robotic architecture. The cloud robotic architecture leverages the combination of an ad-hoc cloud formed by machine-to-machine (M2M) communications among participating robots, and an infrastructure cloud enabled by machine-to-cloud (M2C) communications. Cloud robotics utilizes an elastic computing model, in which resources are dynamically allocated from a shared resource pool in the ubiquitous cloud, to support task offloading and information sharing in robotic applications. We propose and evaluate communication protocols, and several elastic computing models to handle different applications. We discuss the technical challenges in computation, communications and security, and illustrate the potential benefits of cloud robotics in different applications.
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paper_title: Development of a Socially Believable Multi-Robot Solution from Town to Home

paper_content:

Technological advances in the robotic and ICT fields represent an effective solution to address specific societal problems to support ageing and independent life. One of the key factors for these technologies is that they have to be socially acceptable and believable to the end-users. This paper aimed to present some technological aspects that have been faced to develop the Robot-Era system, a multi-robotic system that is able to act in a socially believable way in the environments daily inhabited by humans, such as urban areas, buildings and homes. In particular, this paper focuses on two services—shopping delivery and garbage collection—showing preliminary results on experiments conducted with 35 elderly people. The analysis adopts an end-user-oriented perspective, considering some of the main attributes of acceptability: usability, attitude, anxiety, trust and quality of life.
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Title: Robot–City Interaction: Mapping the Research Landscape—A Survey of the Interactions Between Robots and Modern Cities

Section 1: Research Methodology
Description 1: This section describes the methodology used to conduct the literature survey, including search and selection criteria and core terminology definitions.

Section 2: Core Terminology
Description 2: This section explains the main terminology of the study such as city, robot, and interaction.

Section 3: Search and Selection Criteria
Description 3: This section outlines the criteria for searching and selecting the relevant literature, including time-span, relevant areas, and keyword combinations.

Section 4: The RCI Analytical Framework
Description 4: This section introduces the analytical framework used for reviewing the literature, detailing the four key contexts: agent, urban, information, and interaction.

Section 5: Literature Synthesis
Description 5: This section provides a synthesis of the selected literature according to the four analytical contexts and identifies different RCI areas.

Section 6: The RCI Research Landscape
Description 6: This section characterizes the research landscape of Robot-City Interaction, highlighting its main characteristics and challenges.

Section 7: Summary
Description 7: This section summarizes the findings from the literature review and discusses how the understanding of RCI has evolved through the study.

Section 8: Main Characteristics of RCI
Description 8: This section identifies the main characteristics and challenges of Robot-City Interaction based on the literature review findings.

Section 9: RCI: A Research Landscape
Description 9: This section suggests future directions for research in RCI, focusing on infrastructure, data, knowledge-based environments, and ethical regulations.

Section 10: Relation of RCI to Other Fields
Description 10: This section discusses how RCI relates to and differs from closely related fields such as Ambient Intelligence, Urban Robotics, HRI, and others.

Section 11: Conclusions
Description 11: This section concludes the survey, summarizing the key themes, gaps, and providing guidelines and challenges for future RCI research.