An Overview of 3D Object Grasp Synthesis Algorithms
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paper_title: On the stability of grasped objects

paper_content:

A grasped object is defined to be in equilibrium if the sum of all forces and moments acting on a body equals zero. An equilibrium grasp may be stable or unstable. Force closed grasps are a well-known subset of equilibrium grasps, and they are known to be stable. However, not all stable grasps are force closed, including many common and easily obtainable grasps. In this paper, we classify the categories of equilibrium grasps and establish a general framework for the determination of the stability of a grasp. In order to analyze the stability of grasps with multiple contacts, we first model the compliance at each contact. We develop expressions for the changes in contact forces as a function of the rigid body relative motion between the fingers and the grasped object. The stability of a grasp is shown to depend on the local curvature of the contacting bodies, as well as the magnitude and arrangement of the contact forces. We then derive results providing simple criteria to determine the stability of a grasped object, including the special but important limiting case of rigid bodies where the contact compliance is zero.
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paper_title: Constructing Force- Closure Grasps

paper_content:

This paper presents fast and simple algorithms for directly constructing force-closure grasps based on the shape of the grasped object. The synthesis of force-closure grasps finds in dependent regions of contact for the fingertips, such that the motion of the grasped object is totally constrained. A force- closure grasp implies equilibrium grasps exist. In the reverse direction, we show that most nonmarginal equilibrium grasps are force-closure grasps.
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paper_title: The condition for contact grasp stability

paper_content:

The author distinguishes between two types of grasp stability, called spatial grasp stability and contact grasp stability. The former is the tendency of the grasped object to return to an equilibrium location in space; the latter is the tendency of the points of contact to return to an equilibrium position on the object's surface. It is shown, via examples, that spatial stability cannot capture certain intuitive concepts of grasp stability, and hence that any full understanding of grasp stability must include contact stability. A model of how the positions of the points of contact evolve in time on the surface of the grasped object in the absence of any external force or active feedback is derived. From this model, a condition is obtained which determines whether or not a two-fingered grasp is contact stable. >
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paper_title: On computing three-finger force-closure grasps of polygonal objects

paper_content:

This paper presents a new approach to the computation of stable grasps of polygonal objects. The authors consider the case of a hand equipped with three hard fingers and assume point contact with friction. They prove a sufficient condition for force-closure grasps that leads to a system of linear constraints in the position of the fingers along the polygonal edges. All regions satisfying these constraints are found by a new projection algorithm based on linear parameter elimination accelerated by simplex techniques. Maximal object segments where fingers can be positioned independently are found by linear optimization within the grasp regions. The approach has been implemented and examples are presented. >
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paper_title: Distributed impedance control of multiple robot systems

paper_content:

This paper proposes the distributed impedance approach as a new formulation of multiple robot systems control. In this approach, each cooperating manipulator is provided with its own independent impedance controller. In addition, along selected degrees of freedom, force control is achieved through an external loop, in order to improve control of the object's internal loading. Extensive stability analysis is performed based on a realistic model that includes robots impedance and object dynamics. Experiments are performed using two cooperating industrial robots holding an object through point contacts. Force and position control actions are suitably dispatched to achieve both internal loading control and object position control. The performance of the system is demonstrated for transporting tasks.
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paper_title: On the Closure Properties of Robotic Grasping

paper_content:

The form-closure and force-closure properties of robotic grasp ing are investigated. Loosely speaking, these properties are related to the capability of the robot to inhibit motions of the workpiece in spite of externally applied forces. In this article, form-closure is considered as a purely geometric property of a set of unilateral (contact) constraints, such as those applied on a workpiece by a mechanical fixture, while force-closure is related to the capability of the particular robotic device being considered to apply forces through contacts. The concepts of partial form- and force-closure properties are introduced and discussed, and an algorithm is proposed to obtain a synthetic geometric description of partial form-closure constraints. Al though the literature abounds with form-closure tests, proposed algorithms for testing force-closure are either approximate or computationally expensive. This article proves the equiva lence of force-closure analysis with the study of the equilibria of an ordinary...
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paper_title: On the stability and instantaneous velocity of grasped frictionless objects

paper_content:

An efficient quantitative test for form closure valid for any number of contact points is formulated as a linear program, the optimal objective value of which provides a measure of how far a grasp is from losing form closure. When the grasp does not have form closure, manipulation planning requires a means for predicting the object's stability and instantaneous velocity, given the joint velocities of the hand. The classical approach to computing these quantities is to solve the systems of kinematic inequalities corresponding to all possible combinations of separating or sliding at the contacts. All combinations resulting in the interpenetration of bodies or the infeasibility of the equilibrium equations are rejected. The remaining combination is consistent with all the constraints and is used to compute the velocity of the manipulated object and the contact forces, which indicate whether or not the object is stable. A linear program whose solution yields the same information as the classical approach, usually without explicit testing of all possible combinations of contact interactions, is formulated. >
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paper_title: Computing n-Finger Form-Closure Grasps on Polygonal Objects

paper_content:

This paper presents an efficient algorithm for computing all n-finger form-closure grasps on a polygonal object based on a new sufficient and necessary condition for form-closure. With this new condition, it is possible to transfer the problem of computing the form-closure grasp in R3 to one in R1. We demonstrate that the non-form-closure grasps consist of two convex polytopes in the space of n parameters representing grasp points on sides of the polygon. The proposed algorithm works efficiently for n ≤ 3 and takes O(n3n/2) time for n > 3, where n denotes the number of the fingers. The algorithm has been implemented and its efficiency has been confirmed with two examples.
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paper_title: Synthesis of Force-Closure Grasps on 3-D Objects Based on the Q Distance

paper_content:

The synthesis of force-closure grasps on three-dimensional (3-D) objects is a fundamental issue in robotic grasping and dextrous manipulation. In this paper, a numerical force-closure test is developed based on the concept of Q distance. With some mild and realistic assumptions, the proposed test criterion is differentiable almost everywhere and its derivative can be calculated exactly. On this basis, we present an algorithm for planning force-closure grasps, which is implemented by applying descent search to the proposed numerical test in the grasp configuration space. The algorithm is generally applicable to planning optimal force-closure grasps on 3-D objects with curved surfaces and with arbitrary number of contact points. The effectiveness and efficiency of the algorithm are demonstrated by using simulation examples.
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paper_title: Constructing stable grasps in 3D

paper_content:

This paper presents fast and simple algorithms for directly constructing stable grasps in 3D. The synthesis of stable grasps constructs virtual springs at the contacts, such that the grasped object is stable, and has a desired stiffness matrix about its stable equilibrium. The paper develops a simple geometric relation between the stiffness of the grasp and the spatial configuration of the virtual springs at the contacts. The stiffness of the grasp also depends on whether the points of contact stick, or slide without friction on the edges of the object.
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paper_title: Generalized stability of compliant grasps

paper_content:

We develop a geometric framework for the stability analysis of multifingered grasps and propose a measure of grasp stability for arbitrary perturbations and loading conditions. The measure requires a choice of metric on the group of rigid body displacements. We show that although the stability of a grasp itself does not depend on the choice of metric, comparison of the stability of different grasps depends on the metric. Finally, we provide some insight into the choice of metrics for stability analysis.
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paper_title: Liapunov Stability of Force-Controlled Grasps with a Multi-Fingered Hand

paper_content:

Holding an object stably is a building block for dexterous manipulation with a multi-fingered hand. In recent years a rather large body of literature related to this topic has developed. These works isolate some desired property of a grasp and use this property as the definition of stable grasp. To varying degrees, these approaches ignore the system dynamics. The purpose of this article is to put grasp stability on a more basic and fundamental foundation by defining grasp stability in terms of the well-established stability theory of differential equations. This approach serves to unify the field and to bring a large body of knowledge to bear on the field. Some relationships between the stability concepts used here and the previously used grasp stability concepts are discussed. A hierarchy of three levels of approach to the problem is treated. We consider that the grasp force applied is a basic consideration, in terms of ensuring both that there is sufficient force to prevent dropping the object and that the forces are not too large to cause breakage. As a result, we first investigate the use of constant force grasps. It is shown that with the proper combination of finger locations and grasp forces, such grasps can be Liapunov stable, and methods are presented that help find such grasps. It is also shown that such grasps cannot be asymptotically stable. To produce asymptotic stability, one must alter the forces applied to an object when the object deviates from equilibrium, and a linear feedback force law is given for this. It results in local asymptotic stability guaranteeing convergence to the desired grasp equilibrium from all states within a region of attraction in the state space. Some of the results are similar to results obtained previously, but this time they have a stronger meaning in terms of the dynamic response of the system. In the third level, a nonlinear force law is given that, to within certain limitations, produces global asymptotic grasp stability, so that all initial states are guaranteed to converge to the desired grasp equilibrium. The method is robust to large classes of inaccuracies in the implementation.
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paper_title: Robotic grasping and contact: a review

paper_content:

In this paper, we survey the field of robotic grasping and the work that has been done in this area over the last two decades, with a slight bias toward the development of the theoretical framework and analytical results in this area.
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paper_title: On computing immobilizing grasps of 3-D curved objects

paper_content:

We propose an algorithm for searching a form-closure grasp on a 3-D discretized curved object. The algorithm first randomly selects an initial set of seven contacts from the large collection of candidate contacts and check its form-closure property by the test algorithm developed in our early work. For the non-form-closure grasp, the candidate contacts are classified into set S where the contact wrenches lie on the same side of the separating facet as the initial wrenches and set D where the contact wrenches lie on the different side. The separating facet can be calculated through the test algorithm. Then the initial seven contacts are iteratively improved by exchanging with the candidate contacts in set D. The best-first motion together with random motion are used in the exchange procedure to ensure the convex hull of the seven contact wrenches will approach the origin step by step until the origin is completely contained. Finally, the algorithm has been implemented and its efficiency has been ascertained by three examples.
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paper_title: On computing robust n-finger force-closure grasps of 3D objects

paper_content:

The paper deals with computing frictional force-closure grasps of 3D objects problem. The key idea of the presented work is the demonstration that wrenches associated to any three non-aligned contact points of 3D objects form a basis of their corresponding wrench space. This result permits the formulation of a new sufficient force-closure test. Our approach works with general objects, modelled with a set of points, and with any number n of contacts (n e 4). A quality criterion is also introduced. A corresponding algorithm for computing robust force-closure grasps has been developed. Its efficiency is confirmed by comparing it to the classical convex-hull method [26].
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paper_title: On Computing Four-Finger Equilibrium and Force-Closure Grasps of Polyhedral Objects

paper_content:

This article addresses the problem of computing stable grasps of three-dimensional polyhedral objects. We consider the case of a hand equipped with four hard fingers and assume point contact with friction. We prove new necessary and sufficient conditions for equilibrium and force closure, and present a geometric characterization of all possible types of four-finger equilibrium grasps. We then focus on concurrent grasps, for which the lines of action of the four contact forces all intersect in a point. In this case, the equilibrium conditions are linear in the unknown grasp parameters, which reduces the problem of computing the stable grasp regions in configuration space to the problem of constructing the eight-dimensional projec tion of an ll-dimensinnal polytope. We present two projection methods: the first one uses a simple Gaussian elimination ap proach, while the second one relies on a novel output-sensitive contour-tracking algorithm. Finally, we use linear optimization within the valid configuration...
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paper_title: Qualitative test and force optimization of 3-D frictional form-closure grasps using linear programming

paper_content:

This paper formalizes qualitative test of 3D frictional form-closure grasps of n robotic fingers as a problem of linear programming (LP). It is well-known that a sufficient and necessary condition for form-closure grasps is that the origin of the wrench space lies inside the convex hull of primitive contact wrenches. We demonstrate that the problem of querying whether the origin lies inside the convex hull is equivalent to a ray-shooting problem, which is dual to a LP problem based on the duality between convex hulls and convex polytopes. Furthermore, this paper addresses a problem of minimizing the L/sub 1/ norm of the grasp forces balancing an external wrench, which can be also transformed to a ray-shooting problem. We have implemented the algorithms and confirmed their real-time efficiency for qualitative test and grasp force optimization.
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paper_title: Constructing stable grasps in 3D

paper_content:

This paper presents fast and simple algorithms for directly constructing stable grasps in 3D. The synthesis of stable grasps constructs virtual springs at the contacts, such that the grasped object is stable, and has a desired stiffness matrix about its stable equilibrium. The paper develops a simple geometric relation between the stiffness of the grasp and the spatial configuration of the virtual springs at the contacts. The stiffness of the grasp also depends on whether the points of contact stick, or slide without friction on the edges of the object.
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paper_title: On characterizing and computing three- and four-finger force-closure grasps of polyhedral objects

paper_content:

The problem of characterizing the force-closure grasps of a three-dimensional object by a hand equipped with three or four hard fingers is addressed. Several necessary and several sufficient conditions for force-closure are proved. For polyhedral objects, sufficient conditions that are linear in the unknown parameters are proved. This reduces the problem of computing force-closure grasps of polyhedral objects to the problem of projecting a polytope onto some linear subspace. An efficient, output-sensitive algorithm is presented for computing the projection, together with an algorithm using linear programming for computing maximal grasp regions. >
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paper_title: Automatic grasp planning using shape primitives

paper_content:

Automatic grasp planning for robotic hands is a difficult problem because of the huge number of possible hand configurations. However, humans simplify the problem by choosing an appropriate prehensile posture appropriate for the object and task to be performed. By modeling an object as a set of shape primitives, such as spheres, cylinders, cones and boxes, we can use a set of rules to generate a set of grasp starting positions and pregrasp shapes that can then be tested on the object model. Each grasp is tested and evaluated within our grasping simulator "GraspIt!", and the best grasps are presented to the user. The simulator can also plan grasps in a complex environment involving obstacles and the reachability constraints of a robot arm.
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paper_title: Synthesis of Force-Closure Grasps on 3-D Objects Based on the Q Distance

paper_content:

The synthesis of force-closure grasps on three-dimensional (3-D) objects is a fundamental issue in robotic grasping and dextrous manipulation. In this paper, a numerical force-closure test is developed based on the concept of Q distance. With some mild and realistic assumptions, the proposed test criterion is differentiable almost everywhere and its derivative can be calculated exactly. On this basis, we present an algorithm for planning force-closure grasps, which is implemented by applying descent search to the proposed numerical test in the grasp configuration space. The algorithm is generally applicable to planning optimal force-closure grasps on 3-D objects with curved surfaces and with arbitrary number of contact points. The effectiveness and efficiency of the algorithm are demonstrated by using simulation examples.
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paper_title: Modeling manufacturing grips and correlations with the design of robotic hands

paper_content:

This paper represents the first part of an effort to codify the knowledge required for manipulation tasks in a small-batch manufacturing cell. The motivation for this work is to pave the way for robots that can independently determine how to grasp and manipulate parts in a limited environment and to facilitate the design of advanced, but cost-effective manufacturing hands. We begin with an examination of grasps used by humans working with tools and metal parts. The grips are compared in terms of power, contact area, friction, damping and tactile sensitivity. The comparison leads to a grip taxonomy in which grasps are mapped against task-related quantities (such as power) and object-related quantities (such as slenderness). The examinations of the task requirements and grasps suggest a number of general principles for the design and control of manufacturing hands.
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paper_title: Examples of 3D grasp quality computations

paper_content:

Previous grasp quality research is mainly theoretical, and has assumed that contact types and positions are given, in order to preserve the generality of the proposed quality measures. The example results provided by these works either ignore hand geometry and kinematics entirely or involve only the simplest of grippers. We present a unique grasp analysis system that, when given a 3D object, hand, and pose for the hand, can accurately determine the types of contacts that will occur between the links of the hand and the object, and compute two measures of quality for the grasp. Using models of two articulated robotic hands, we analyze several grasps of a polyhedral model of a telephone handset, and we use a novel technique to visualize the 6D space used in these computations. In addition, we demonstrate the possibility of using this system for synthesizing high quality grasps by performing a search over a subset of possible hand configurations.
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paper_title: Fast planning of precision grasps for 3D objects

paper_content:

In the near future, more and more robots will be used for servicing tasks, tasks in hazardous environments or space applications. Dextrous hands are a powerful and flexible tool to interact with these real world environments that are not specially tailored for robots. In order to grasp and manipulate real world objects, grasp planning systems are required. Grasp planning for general 3D objects is quite a complex problem requiring a large amount of computing time. Fast algorithms are required to integrate grasp planners in online planning systems for robots. This paper presents an heuristic approach towards fast planning of precision grasps for realistic, arbitrarily shaped 3D objects. In this approach a number of feasible grasp candidates are generated heuristically. These grasp candidates are qualified using an efficiently computable grasp quality measure and the best candidate is chosen. It is shown that only a relatively small number of grasp candidates has to be generated in order to obtain a good-although not optimal-grasp.
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paper_title: Grasping the dice by dicing the grasp

paper_content:

Many methods for generating and analyzing grasps have been developed in the recent years. They gave insight and comprehension of grasping with robot hands but many of them are rather complicated to implement and of high computational complexity. In this paper we study if the basic quality criterion for grasps, the force-closure property, is in principle easy or difficult to reach. We show that it is not necessary to generate optimal grasps, due to a certain quality measure, for real robot grasping tasks where an average quality grasp is acceptable. We present statistical data that confirm our opinion that a randomized grasp generation algorithm is fast and suitable for the planning of robot grasping tasks.
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paper_title: Task-oriented quality measures for dextrous grasping

paper_content:

We propose a new and efficient approach to compute task oriented quality measures for dextrous grasps. Tasks can be specified as a single wrench to be applied, as a rough direction in form of a wrench cone, or as a complex wrench polytope. Based on the linear matrix inequality formalism to treat the friction cone constraints we formulate respective convex optimization problems, whose solutions give the maximal applicable wrench in the task direction together with the needed contact forces. Numerical experiments show that application to complex grasps with many contacts is possible.
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paper_title: Manipulability of Robotic Mechanisms

paper_content:

This paper discusses the manipulating ability of robotic mechanisms in positioning and orienting end-effectors and proposes a measure of manipulability. Some properties of this measure are obtained, the best postures of various types of manipulators are given, and a four-degree-of-freedom finger is considered from the viewpoint of the measure. The pos tures somewhat resemble those of human arms and fingers.
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paper_title: Task-Oriented Grasping using Hand Preshapes and Task Frames

paper_content:

In this paper we present a robot that is able to perform daily manipulation tasks in a home environment, such as opening doors and drawers. Taking as input a simplified object model and the task to perform, the robot automatically finds a grasp suitable for the task and performs it. For this, we identify a set of hand preshapes and classify them according to the grasp wrench space they generate. Given a task, the robot selects the most suitable hand preshape and automatically plans a set of actions in order to reach the object and to perform the task, taking continuously into account the task forces. The concept of hand preshape is extended for the inclusion of a task frame, which is a concept from task planning, thus filling the gap between the grasp and the task.
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paper_title: Task oriented optimal grasping by multifingered robot hands

paper_content:

We discuss the problem of optimal grasping to an object by a multifingered robot hand. We axiomatize using screw theory and elementary differential geometry the concept of a grasp and characterize its stability. Three quality measures for evaluating a grasp are then proposed. The last quality measure is task oriented and needs the development of a procedure for modeling tasks as ellipsoids in the wrench space of the object. Numerical computations of these quality measures and the selection of an optimal grasp are addressed in detail. Several examples are given using these quality measures to show that they are consistent with human grasping experience.
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paper_title: Robot manipulability

paper_content:

This paper demonstrates fundamental problems with dexterity measures found throughout the robotics literature and offers a methodology for correcting those problems. Measures of robot dexterity derived from eigenvalues, eigenvectors, similarity transformations, singular-value decompositions and the Moore-Penrose inverse of the manipulator Jacobian do not have invariant physical meaning. The paper presents manipulability ellipsoids and manipulability screw-subspaces for both redundant and nonredundant manipulators. >
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paper_title: Task Compatibility of Manipulator Postures

paper_content:

In performing a manipulation task, humans tend to adopt arm postures that most effectively utilize the motion and strength capabilities of the arm. Selecting arm postures that are compatible with the task requirements has become almost instinctive to humans. By mimicking this approach in robotic manipulation, we can exploit the full capability of a manipu lator in performing a task. An index is proposed for measur ing the compatibility of manipulator postures with respect to a generalized task description. The manipulator is viewed as a mechanical transformer, with joint space velocity and force as input and task space velocity and force as output. Optimi zation of the index corresponds to matching the velocity and force transmission characteristics to the task requirements. The applications of this index to manipulator redundancy utilization and workspace design are also discussed.
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paper_title: Imitation in Animals and Artifacts

paper_content:

The effort to explain the imitative abilities of humans and other animals draws on fields as diverse as animal behavior, artificial intelligence, computer science, comparative psychology, neuroscience, primatology, and linguistics. This volume represents a first step toward integrating research from those studying imitation in humans and other animals, and those studying imitation through the construction of computer software and robots. Imitation is of particular importance in enabling robotic or software agents to share skills without the intervention of a programmer and in the more general context of interaction and collaboration between software agents and humans. Imitation provides a way for the agent -- whether biological or artificial -- to establish a "social relationship" and learn about the demonstrator's actions, in order to include them in its own behavioral repertoire. Building robots and software agents that can imitate other artificial or human agents in an appropriate way involves complex problems of perception, experience, context, and action, solved in nature in various ways by animals that imitate.
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paper_title: A survey of robot learning from demonstration

paper_content:

We present a comprehensive survey of robot Learning from Demonstration (LfD), a technique that develops policies from example state to action mappings. We introduce the LfD design choices in terms of demonstrator, problem space, policy derivation and performance, and contribute the foundations for a structure in which to categorize LfD research. Specifically, we analyze and categorize the multiple ways in which examples are gathered, ranging from teleoperation to imitation, as well as the various techniques for policy derivation, including matching functions, dynamics models and plans. To conclude we discuss LfD limitations and related promising areas for future research.
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paper_title: Computational Approaches to Motor Learning by Imitation

paper_content:

Movement imitation requires a complex set of mechanisms that map an observed movement of a teacher onto one's own movement apparatus. Relevant problems include movement recognition, pose estimation, pose tracking, body correspondence, coordinate transformation from external to egocentric space, matching of observed against previously learned movement, resolution of redundant degrees-of-freedom that are unconstrained by the observation, suitable movement representations for imitation, modularization of motor control, etc. All of these topics by themselves are active research problems in computational and neurobiological sciences, such that their combination into a complete imitation system remains a daunting undertaking-indeed, one could argue that we need to understand the complete perception-action loop. As a strategy to untangle the complexity of imitation, this paper will examine imitation purely from a computational point of view, i.e. we will review statistical and mathematical approaches that have been suggested for tackling parts of the imitation problem, and discuss their merits, disadvantages and underlying principles. Given the focus on action recognition of other contributions in this special issue, this paper will primarily emphasize the motor side of imitation, assuming that a perceptual system has already identified important features of a demonstrated movement and created their corresponding spatial information. Based on the formalization of motor control in terms of control policies and their associated performance criteria, useful taxonomies of imitation learning can be generated that clarify different approaches and future research directions.
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paper_title: Learning techniques in a dataglove based telemanipulation system for the DLR hand

paper_content:

We present a setup to control a four-finger anthropomorphic robot hand using a dataglove. To be able to accurately use the dataglove we implemented a nonlinear learning calibration using a novel neural network technique. Experiments show that a resulting positioning error not exceeding 1.8 mm, but typically 0.5 mm, per finger can be obtained; this accuracy is sufficiently precise for grasping tasks. Based on the dataglove calibration we present a solution for the mapping of human and artificial hand workspaces that enables an operator to intuitively and easily telemanipulate objects with the artificial hand.
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paper_title: Detection and evaluation of grasping positions for autonomous agents

paper_content:

The action of grasping an object is very important for a humanoid agent with hand, evolving autonomously in a virtual world. If an agent is given the order "grasp the object", he has to determine the portion of the object to grasp. In order to determine a grasping position, it is necessary to recognize the form of the 3-dimensional geometry, and detect portions which are suitable for grasp. Assuming that the object is grasped by one hand, we propose two techniques for detecting appropriate portions to be grasped on the surface of an object and for generating the grasping postures. In this paper, our main contributions are as follows: the first is the detection of appropriate portions to be grasped on the surface of an object; the second is the formation of the hand shape to grasp various shaped objects. Using the two proposing methods, grasped positions and the hand shapes for each of them are computed. Moreover, these positions are evaluated by their stabilities using the robotics technique
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paper_title: Human-to-Robot Mapping of Grasps

paper_content:

We are developing a Programming by Demonstration (PbD) system for which recognition of objects and pick-and-place actions represent basic building blocks for task learning. An important capability in this system is automatic isual recognition of human grasps, and methods for mapping the human grasps to the functionally corresponding robot grasps. This paper describes the grasp recognition system, focusing on the human-to-robot mapping. The visual grasp classification and grasp orientation regression is described in our IROS 2008 paper [1]. In contrary to earlier approaches, no articulated 3D reconstruction of the hand over time is taking place. The input data consists of a single image of the human hand. The hand shape is classified as one of six grasps by finding similar hand shapes in a large database of grasp images. From the database, the hand orientation is also estimated. The recognized grasp is then mapped to one of three predefined Barrett hand grasps. Depending on the type of robot grasp, a precomputed grasp strategy is selected. The strategy is further parameterized by the orientation of the hand relative to the environment show purposes.
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paper_title: Robot grasp synthesis from virtual demonstration and topology-preserving environment reconstruction

paper_content:

Automatic environment modeling is an essential requirement for intelligent robots to execute manipulation tasks. Object recognition and workspace reconstruction also enable 3D user interaction and programming of assembly operations. In this paper a novel method for synthesizing robot grasps from demonstration is presented. The system allows learning and classification of human grasps demonstrated in virtual reality as well as teaching of robot grasps and simulation of manipulation tasks. Both virtual grasp demonstration and grasp synthesis take advantage of a topology-preserving approach for automatic workspace modeling with a monocular camera. The method is based on the computation of edge-face graphs. The algorithm works in real-time and shows high scalability in the number of objects thus allowing accurate reconstruction and registration from multiple views. Grasp synthesis is performed mimicking the human hand pre-grasp motion with data smoothing. Experiments reported in the paper have tested the capabilities of both the vision algorithm and the grasp synthesizer.
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paper_title: Learning techniques in a dataglove based telemanipulation system for the DLR hand

paper_content:

We present a setup to control a four-finger anthropomorphic robot hand using a dataglove. To be able to accurately use the dataglove we implemented a nonlinear learning calibration using a novel neural network technique. Experiments show that a resulting positioning error not exceeding 1.8 mm, but typically 0.5 mm, per finger can be obtained; this accuracy is sufficiently precise for grasping tasks. Based on the dataglove calibration we present a solution for the mapping of human and artificial hand workspaces that enables an operator to intuitively and easily telemanipulate objects with the artificial hand.
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paper_title: Learning and Evaluation of the Approach Vector for Automatic Grasp Generation and Planning

paper_content:

In this paper, we address the problem of automatic grasp generation for robotic hands where experience and shape primitives are used in synergy so to provide a basis not only for grasp generation but also for a grasp evaluation process when the exact pose of the object is not available. One of the main challenges in automatic grasping is the choice of the object approach vector, which is dependent both on the object shape and pose as well as the grasp type. Using the proposed method, the approach vector is chosen not only based on the sensory input but also on experience that some approach vectors will provide useful tactile information that finally results in stable grasps. A methodology for developing and evaluating grasp controllers is presented where the focus lies on obtaining stable grasps under imperfect vision. The method is used in a teleoperation or a programming by demonstration setting where a human demonstrates to a robot how to grasp an object. The system first recognizes the object and grasp type which can then be used by the robot to perform the same action using a mapped version of the human grasping posture.
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paper_title: Modeling manufacturing grips and correlations with the design of robotic hands

paper_content:

This paper represents the first part of an effort to codify the knowledge required for manipulation tasks in a small-batch manufacturing cell. The motivation for this work is to pave the way for robots that can independently determine how to grasp and manipulate parts in a limited environment and to facilitate the design of advanced, but cost-effective manufacturing hands. We begin with an examination of grasps used by humans working with tools and metal parts. The grips are compared in terms of power, contact area, friction, damping and tactile sensitivity. The comparison leads to a grip taxonomy in which grasps are mapped against task-related quantities (such as power) and object-related quantities (such as slenderness). The examinations of the task requirements and grasps suggest a number of general principles for the design and control of manufacturing hands.
---
paper_title: Human-to-Robot Mapping of Grasps

paper_content:

We are developing a Programming by Demonstration (PbD) system for which recognition of objects and pick-and-place actions represent basic building blocks for task learning. An important capability in this system is automatic isual recognition of human grasps, and methods for mapping the human grasps to the functionally corresponding robot grasps. This paper describes the grasp recognition system, focusing on the human-to-robot mapping. The visual grasp classification and grasp orientation regression is described in our IROS 2008 paper [1]. In contrary to earlier approaches, no articulated 3D reconstruction of the hand over time is taking place. The input data consists of a single image of the human hand. The hand shape is classified as one of six grasps by finding similar hand shapes in a large database of grasp images. From the database, the hand orientation is also estimated. The recognized grasp is then mapped to one of three predefined Barrett hand grasps. Depending on the type of robot grasp, a precomputed grasp strategy is selected. The strategy is further parameterized by the orientation of the hand relative to the environment show purposes.
---
paper_title: Imitation in Animals and Artifacts

paper_content:

The effort to explain the imitative abilities of humans and other animals draws on fields as diverse as animal behavior, artificial intelligence, computer science, comparative psychology, neuroscience, primatology, and linguistics. This volume represents a first step toward integrating research from those studying imitation in humans and other animals, and those studying imitation through the construction of computer software and robots. Imitation is of particular importance in enabling robotic or software agents to share skills without the intervention of a programmer and in the more general context of interaction and collaboration between software agents and humans. Imitation provides a way for the agent -- whether biological or artificial -- to establish a "social relationship" and learn about the demonstrator's actions, in order to include them in its own behavioral repertoire. Building robots and software agents that can imitate other artificial or human agents in an appropriate way involves complex problems of perception, experience, context, and action, solved in nature in various ways by animals that imitate.
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paper_title: Improved Switching among Temporally Abstract Actions

paper_content:

In robotics and other control applications it is commonplace to have a preexisting set of controllers for solving subtasks, perhaps hand-crafted or previously learned or planned, and still face a difficult problem of how to choose and switch among the controllers to solve an overall task as well as possible. In this paper we present a framework based on Markov decision processes and semi-Markov decision processes for phrasing this problem, a basic theorem regarding the improvement in performance that can be obtained by switching flexibly between given controllers, and example applications of the theorem. In particular, we show how an agent can plan with these high-level controllers and then use the results of such planning to find an even better plan, by modifying the existing controllers, with negligible additional cost and no re-planning. In one of our examples, the complexity of the problem is reduced from 24 billion state-action pairs to less than a million state-controller pairs.
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paper_title: Detection and evaluation of grasping positions for autonomous agents

paper_content:

The action of grasping an object is very important for a humanoid agent with hand, evolving autonomously in a virtual world. If an agent is given the order "grasp the object", he has to determine the portion of the object to grasp. In order to determine a grasping position, it is necessary to recognize the form of the 3-dimensional geometry, and detect portions which are suitable for grasp. Assuming that the object is grasped by one hand, we propose two techniques for detecting appropriate portions to be grasped on the surface of an object and for generating the grasping postures. In this paper, our main contributions are as follows: the first is the detection of appropriate portions to be grasped on the surface of an object; the second is the formation of the hand shape to grasp various shaped objects. Using the two proposing methods, grasped positions and the hand shapes for each of them are computed. Moreover, these positions are evaluated by their stabilities using the robotics technique
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paper_title: An SVM learning approach to robotic grasping

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Finding appropriate stable grasps for a hand (either robotic or human) on an arbitrary object has proved to be a challenging and difficult problem. The space of grasping parameters coupled with the degrees-of-freedom and geometry of the object to be grasped creates a high-dimensional, non-smooth manifold. Traditional search methods applied to this manifold are typically not powerful enough to find appropriate stable grasping solutions, let alone optimal grasps. We address this issue in this paper, which attempts to find optimal grasps of objects using a grasping simulator. Our unique approach to the problem involves a combination of numerical methods to recover parts of the grasp quality surface with any robotic hand, and contemporary machine learning methods to interpolate that surface, in order to find the optimal grasp.
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paper_title: Robotic Grasping of Novel Objects using Vision

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We consider the problem of grasping novel objects, specifically objects that are being seen for the first time through vision. Grasping a previously unknown object, one for which a 3-d model is not available, is a challenging problem. Furthermore, even if given a model, one still has to decide where to grasp the object. We present a learning algorithm that neither requires nor tries to build a 3-d model of the object. Given two (or more) images of an object, our algorithm attempts to identify a few points in each image corresponding to good locations at which to grasp the object. This sparse set of points is then triangulated to obtain a 3-d location at which to attempt a grasp. This is in contrast to standard dense stereo, which tries to triangulate every single point in an image (and often fails to return a good 3-d model). Our algorithm for identifying grasp locations from an image is trained by means of supervised learning, using synthetic images for the training set. We demonstrate this approach on two robotic manipulation platforms. Our algorithm successfully grasps a wide variety of objects, such as plates, tape rolls, jugs, cellphones, keys, screwdrivers, staplers, a thick coil of wire, a strangely shaped power horn and others, none of which were seen in the training set. We also apply our method to the task of unloading items from dishwashers.
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paper_title: Planning optimal grasps

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The authors address the problem of planning optimal grasps. Two general optimality criteria that consider the total finger force and the maximum finger force are introduced and discussed. Their formalization using various metrics on a space of generalized forces is detailed. The geometric interpretation of the two criteria leads to an efficient planning algorithm. An example of its use in a robotic environment equipped with two-jaw and three-jaw is described. >
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paper_title: Learning Grasping Points with Shape Context

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This paper presents work on vision based robotic grasping. The proposed method adopts a learning framework where prototypical grasping points are learnt from several examples and then used on novel objects. For representation purposes, we apply the concept of shape context and for learning we use a supervised learning approach in which the classifier is trained with labelled synthetic images. We evaluate and compare the performance of linear and non-linear classifiers. Our results show that a combination of a descriptor based on shape context with a non-linear classification algorithm leads to a stable detection of grasping points for a variety of objects.
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paper_title: Functional Object Class Detection Based on Learned Affordance Cues

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Current approaches to visual object class detection mainly focus on the recognition of basic level categories, such as cars, motorbikes, mugs and bottles. Although these approaches have demonstrated impressive performance in terms of recognition, their restriction to these categories seems inadequate in the context of embodied, cognitive agents. Here, distinguishing objects according to functional aspects based on object affordances is important in order to enable manipulation of and interaction between physical objects and cognitive agent. ::: ::: In this paper, we propose a system for the detection of functional object classes, based on a representation of visually distinct hints on object affordances (affordance cues). It spans the complete range from tutordriven acquisition of affordance cues, learning of corresponding object models, and detecting novel instances of functional object classes in real images.
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paper_title: Data-Driven Grasp Synthesis Using Shape Matching and Task-Based Pruning

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Human grasps, especially whole-hand grasps, are difficult to animate because of the high number of degrees of freedom of the hand and the need for the hand to conform naturally to the object surface. Captured human motion data provides us with a rich source of examples of natural grasps. However, for each new object, we are faced with the problem of selecting the best grasp from the database and adapting it to that object. This paper presents a data-driven approach to grasp synthesis. We begin with a database of captured human grasps. To identify candidate grasps for a new object, we introduce a novel shape matching algorithm that matches hand shape to object shape by identifying collections of features having similar relative placements and surface normals. This step returns many grasp candidates, which are clustered and pruned by choosing the grasp best suited for the intended task. For pruning undesirable grasps, we develop an anatomically-based grasp quality measure specific to the human hand. Examples of grasp synthesis are shown for a variety of objects not present in the original database. This algorithm should be useful both as an animator tool for posing the hand and for automatic grasp synthesis in virtual environments.
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paper_title: A hybrid approach for grasping 3D objects

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The paper presents a novel strategy that learns to associate a grasp to an unknown object/task. A hybrid approach combining empirical and analytical methods is proposed. The empirical step ensures task-compatibility by learning to identify the object graspable part in accordance with humans choice. The analytical step permits contact points generation guaranteeing the grasp stability. The robotic hand kinematics are also taken into account. The corresponding results are illustrated using GraspIt interface [1].
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paper_title: A new strategy combining empirical and analytical approaches for grasping unknown 3D objects

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This paper proposes a novel strategy for grasping 3D unknown objects in accordance with their corresponding task. We define the handle or the natural grasping component of an object as the part chosen by humans to pick up this object. When humans reach out to grasp an object, it is generally in the aim of accomplishing a task. Thus, the chosen grasp is quite related to the object task. Our approach learns to identify object handles by imitating humans. In this paper, a new sufficient condition for computing force-closure grasps on the obtained handle is also proposed. Several experiments were conducted to test the ability of the algorithm to generalize to new objects. They also show the adaptability of our strategy to the hand kinematics.
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Title: An Overview of 3D Object Grasp Synthesis Algorithms

Section 1: Introduction
Description 1: Provide an introduction to the field of robotic grasping, outlining the goals and challenges of grasp synthesis algorithms.

Section 2: Background and Terminology
Description 2: Explain the basic functions and essential properties of a gripper, including terminology such as equilibrium, stability, force-closure, and form-closure.

Section 3: Analytical Approaches
Description 3: Review grasp synthesis algorithms that are based on analytical approaches involving geometric, kinematic, and dynamic formulations.

Section 4: Force-Closure Grasps
Description 4: Present techniques for finding force-closure grasps for 3D objects, including both force-closure grasp synthesis for 3D objects and optimal force-closure grasp synthesis.

Section 5: Task Compatibility
Description 5: Discuss the importance of task-oriented grasping and the criteria for ensuring that a grasp is suitable for the task at hand.

Section 6: Discussion on Analytical Approaches
Description 6: Analyze the effectiveness and limitations of analytical approaches for grasp synthesis, particularly regarding computational complexity and task-specific adaptability.

Section 7: Empirical Approaches
Description 7: Examine empirical grasping approaches based on classification and learning methods, including those focused on human observation and object observation.

Section 8: Discussion on Empirical Approaches
Description 8: Evaluate the benefits and drawbacks of empirical approaches, and discuss the challenges in achieving natural grasps.

Section 9: Conclusion
Description 9: Summarize the findings of the survey, comparing analytical and empirical approaches, and highlight open problems and future research directions in grasp synthesis.