A survey on unmanned aerial vehicle collision avoidance systems
---
paper_title: A Comparative Study of Collision Avoidance Techniques for Unmanned Aerial Vehicles

paper_content:

In this paper three collision avoidance methods for an unmanned aerial vehicle (UAV) are tested and compared to one another. The quadrocopter dynamic model with attitude and velocity controller, a trajectory generator and a selection of collision avoidance approaches were implemented. The first collision avoidance method is based on a geometric approach which computes a direction of avoidance from the flight direction and simple geometric equations. The second technique uses virtual repulsive force fields causing the UAV to be repelled by obstacles. The last method is a grid-based online path re-planning algorithm with A* search that finds a collision free path during flight. Various flight scenarios were defined including static and dynamic obstacles.
---
paper_title: A survey of collision avoidance approaches for unmanned aerial vehicles

paper_content:

The ability to integrate unmanned and manned aircraft into airspace is a critical capability that will enable growth in wide varieties of applications. Collision avoidance is a key enabler for the integration of manned and unmanned missions in civil and military operation theaters. Large efforts have been done to address collision avoidance problem to both manned and unmanned aircraft. However, there has been little comparative discussion of the proposed approaches. This paper presents a survey of the collision avoidance approaches those deployed for aircraft, especially for unmanned aerial vehicles. The collision avoidance concept is introduced together with proposing generic functions carried by collision avoidance systems. The design factors of the sense and avoid system, which are used to categorize methods, are explained deeply. Based on the design factors, several typical approaches are categorized.
---
paper_title: A survey of collision avoidance approaches for unmanned aerial vehicles

paper_content:

The ability to integrate unmanned and manned aircraft into airspace is a critical capability that will enable growth in wide varieties of applications. Collision avoidance is a key enabler for the integration of manned and unmanned missions in civil and military operation theaters. Large efforts have been done to address collision avoidance problem to both manned and unmanned aircraft. However, there has been little comparative discussion of the proposed approaches. This paper presents a survey of the collision avoidance approaches those deployed for aircraft, especially for unmanned aerial vehicles. The collision avoidance concept is introduced together with proposing generic functions carried by collision avoidance systems. The design factors of the sense and avoid system, which are used to categorize methods, are explained deeply. Based on the design factors, several typical approaches are categorized.
---
paper_title: A Comparative Study of Collision Avoidance Techniques for Unmanned Aerial Vehicles

paper_content:

In this paper three collision avoidance methods for an unmanned aerial vehicle (UAV) are tested and compared to one another. The quadrocopter dynamic model with attitude and velocity controller, a trajectory generator and a selection of collision avoidance approaches were implemented. The first collision avoidance method is based on a geometric approach which computes a direction of avoidance from the flight direction and simple geometric equations. The second technique uses virtual repulsive force fields causing the UAV to be repelled by obstacles. The last method is a grid-based online path re-planning algorithm with A* search that finds a collision free path during flight. Various flight scenarios were defined including static and dynamic obstacles.
---
paper_title: Reactive Vision Based Obstacle Avoidance with Camera Field of View Constraints

paper_content:

The lack of reliable, low power, low weight sensors make automatic obstacle avoidance for fixed wing micro air vehicles (MAV) a difficult problem. Traditional sensors for obstacle detection such as radar are too heavy and too large for MAVs and generating paths around detected obstacles is non-trivial. EO/IRCameras are small and lightweight providing a viable alternative to large sensors. We assume that vision processing provides object segmentation and a range estimate to nearby obstacles. We propose a nonlinear guidance law that directly reacts to image data by pushing the obstacles to the edge of the camera field-of-view, and thus avoiding collision. As the MAV passes the obstacle, the original trajectory is resumed. This method can be used in conjunction with high level path planners.
---
paper_title: Aircraft collision avoidance with potential gradient—ground‐based avoidance for horizontal maneuvers

paper_content:

This paper describes ground-based avoidance for horizontal maneuvers using a concept of potential as a collision avoidance aircraft procedure. First, mathematical formulation is introduced by using potential as a way to systematically represent the conditions contributing to collision avoidance such as a threat of collision with other aircraft and degrees of deviation from the original course. ::: ::: ::: ::: The flight course with a lower potential is considered safer. In the choice of a specific avoidance course, an avoidance pattern generation method by means of potential gradient is shown. the future location of the aircraft is sampled at a certain time interval. the shift of the sampling point corresponding to the potential gradient at each sampling point or the force applied to each sampling point (attractive or repulsive) is repeated. ::: ::: ::: ::: It was confirmed that by means of this method, avoidance patterns without danger of collision can be obtained with only horizontal avoidance except for special cases. However, when the sampling points are symmetric or when more than three aircraft are involved, the procedure is not adequate and some provisions are needed. to this end, the sampling point arrangement in the initial stage before the avoidance pattern is formed and the three-dimensional avoidance including vertical avoidance can be considered.
---
paper_title: A real-time monocular vision-based frontal obstacle detection and avoidance for low cost UAVs in GPS denied environment

paper_content:

This paper presents a novel monocular vision-based realtime obstacle detection and avoidance for a low cost unmanned aerial vehicle (UAV) in an unstructured, GPS denied environment. We propose a mathematical model to estimate the relative distance from the UAV's camera to an obstacle which will subsequently be used in a collision avoidance algorithm. We validate our model with some real time experiments under both stationary and dynamic motion of the UAV during its flight. The results show good agreement with the ground truth values with an acceptable percentage of error in estimation under 3% thus proving it can facilitate obstacle detection and avoidance for low cost and lightweight UAVs.
---
paper_title: Reactive Collision Avoidance for Unmanned Aerial Vehicles Using Doppler Radar

paper_content:

Research into reactive collision avoidance for unmanned aerial vehicles has been conducted on unmanned terrestrial and mini aerial vehicles utilising active Doppler radar obstacle detection sensors. Flight tests conducted by flying a mini UAV at an obstacle have confirmed that a simple reactive collision avoidance algorithm enables aerial vehicles to autonomously avoid obstacles. This builds upon simulation work and results obtained using a terrestrial vehicle that had already confirmed that active sensors and a reactive collision avoidance algorithm are able to successfully find a collision free path through an obstacle field.
---
paper_title: Decision strategies for automated visual collision avoidance

paper_content:

This paper provides a preliminary analysis of an autonomous uncooperative collision avoidance strategy for unmanned aircraft using image-based visual control. Assuming target detection, the approach consists of three parts. First, a novel decision strategy is used to determine appropriate reference image features to track for safe avoidance. This is achieved by considering the current rules of the air (regulations), the properties of spiral motion and the expected visual tracking errors. Second, a spherical visual predictive control (VPC) scheme is used to guide the aircraft along a safe spiral-like trajectory about the object. Lastly, a stopping decision based on thresholding a cost function is used to determine when to stop the avoidance behaviour. The approach does not require estimation of range or time to collision, and instead relies on tuning two mutually exclusive decision thresholds to ensure satisfactory performance.
---
paper_title: UAV collision avoidance using cooperative predictive control

paper_content:

This article describes the use of predictive control for the decentralized cooperative control of unmanned aerial vehicles in an unfamiliar three-dimensional environment. It is assumed that each vehicle is equipped with an autopilot and a trajectory control unit. The autopilot insures the stability of the vehicle. The setpoints of the autopilot are calculated by the trajectory control unit, thus forming a cascade control structure. The trajectory control unit relies on a predictive control algorithm to calculate the optimal commands (autopilot setpoints) such that the vehicle will reach fixed targets at known positions while avoiding static obstacles that are detected en route. The advantage in using predictive control is that it offers great flexibility in the objective function to optimize while respecting constraints such as command limits, limits on the displacement that a vehicle can carry out, and the constraints that allow obstacle avoidance. The principle proposed in order to avoid static obstacles (that are assumed ellipsoid) is to verify that the predicted vehicle trajectory does not intersect these obstacles. With the objective to increase performance, cooperation between vehicles must also be privileged. Thus, if some vehicles are within the communication range, they can share the position and shape of the obstacles they have detected. Simulations illustrate the method and higlight the benefits of cooperation.
---
paper_title: Cooperative sense and avoid: Implementation in simulation and real world for small unmanned aerial vehicles

paper_content:

In this paper we present a framework and a method for sense and avoid to be used with unmanned areial sytems (UAS). The framework is an essential part to develop and validate the sense and avoidance algorithms. It is implemented and used for simulation and on a real system by using a common interface. The avoidance method in this paper is based on the fact that the intruder vehicle has certain limitations in turn rate and acceleration or deceleration. This is used to define the geometry of the threat zone for every intruder. In comparison to other geometry based algorithms the presented method uses the abilities (type) of the intruding aircraft and its current state. Diverse scenarios have been simulated successfully in that framework and code for the real system was generated and implemented.
---
paper_title: Cooperative sense and avoid: Implementation in simulation and real world for small unmanned aerial vehicles

paper_content:

In this paper we present a framework and a method for sense and avoid to be used with unmanned areial sytems (UAS). The framework is an essential part to develop and validate the sense and avoidance algorithms. It is implemented and used for simulation and on a real system by using a common interface. The avoidance method in this paper is based on the fact that the intruder vehicle has certain limitations in turn rate and acceleration or deceleration. This is used to define the geometry of the threat zone for every intruder. In comparison to other geometry based algorithms the presented method uses the abilities (type) of the intruding aircraft and its current state. Diverse scenarios have been simulated successfully in that framework and code for the real system was generated and implemented.
---
paper_title: A Comparative Study of Collision Avoidance Techniques for Unmanned Aerial Vehicles

paper_content:

In this paper three collision avoidance methods for an unmanned aerial vehicle (UAV) are tested and compared to one another. The quadrocopter dynamic model with attitude and velocity controller, a trajectory generator and a selection of collision avoidance approaches were implemented. The first collision avoidance method is based on a geometric approach which computes a direction of avoidance from the flight direction and simple geometric equations. The second technique uses virtual repulsive force fields causing the UAV to be repelled by obstacles. The last method is a grid-based online path re-planning algorithm with A* search that finds a collision free path during flight. Various flight scenarios were defined including static and dynamic obstacles.
---
paper_title: UAV collision avoidance using cooperative predictive control

paper_content:

This article describes the use of predictive control for the decentralized cooperative control of unmanned aerial vehicles in an unfamiliar three-dimensional environment. It is assumed that each vehicle is equipped with an autopilot and a trajectory control unit. The autopilot insures the stability of the vehicle. The setpoints of the autopilot are calculated by the trajectory control unit, thus forming a cascade control structure. The trajectory control unit relies on a predictive control algorithm to calculate the optimal commands (autopilot setpoints) such that the vehicle will reach fixed targets at known positions while avoiding static obstacles that are detected en route. The advantage in using predictive control is that it offers great flexibility in the objective function to optimize while respecting constraints such as command limits, limits on the displacement that a vehicle can carry out, and the constraints that allow obstacle avoidance. The principle proposed in order to avoid static obstacles (that are assumed ellipsoid) is to verify that the predicted vehicle trajectory does not intersect these obstacles. With the objective to increase performance, cooperation between vehicles must also be privileged. Thus, if some vehicles are within the communication range, they can share the position and shape of the obstacles they have detected. Simulations illustrate the method and higlight the benefits of cooperation.
---
paper_title: Reactive Vision Based Obstacle Avoidance with Camera Field of View Constraints

paper_content:

The lack of reliable, low power, low weight sensors make automatic obstacle avoidance for fixed wing micro air vehicles (MAV) a difficult problem. Traditional sensors for obstacle detection such as radar are too heavy and too large for MAVs and generating paths around detected obstacles is non-trivial. EO/IRCameras are small and lightweight providing a viable alternative to large sensors. We assume that vision processing provides object segmentation and a range estimate to nearby obstacles. We propose a nonlinear guidance law that directly reacts to image data by pushing the obstacles to the edge of the camera field-of-view, and thus avoiding collision. As the MAV passes the obstacle, the original trajectory is resumed. This method can be used in conjunction with high level path planners.
---
paper_title: Decision strategies for automated visual collision avoidance

paper_content:

This paper provides a preliminary analysis of an autonomous uncooperative collision avoidance strategy for unmanned aircraft using image-based visual control. Assuming target detection, the approach consists of three parts. First, a novel decision strategy is used to determine appropriate reference image features to track for safe avoidance. This is achieved by considering the current rules of the air (regulations), the properties of spiral motion and the expected visual tracking errors. Second, a spherical visual predictive control (VPC) scheme is used to guide the aircraft along a safe spiral-like trajectory about the object. Lastly, a stopping decision based on thresholding a cost function is used to determine when to stop the avoidance behaviour. The approach does not require estimation of range or time to collision, and instead relies on tuning two mutually exclusive decision thresholds to ensure satisfactory performance.
---
paper_title: Aircraft collision avoidance with potential gradient—ground‐based avoidance for horizontal maneuvers

paper_content:

This paper describes ground-based avoidance for horizontal maneuvers using a concept of potential as a collision avoidance aircraft procedure. First, mathematical formulation is introduced by using potential as a way to systematically represent the conditions contributing to collision avoidance such as a threat of collision with other aircraft and degrees of deviation from the original course. ::: ::: ::: ::: The flight course with a lower potential is considered safer. In the choice of a specific avoidance course, an avoidance pattern generation method by means of potential gradient is shown. the future location of the aircraft is sampled at a certain time interval. the shift of the sampling point corresponding to the potential gradient at each sampling point or the force applied to each sampling point (attractive or repulsive) is repeated. ::: ::: ::: ::: It was confirmed that by means of this method, avoidance patterns without danger of collision can be obtained with only horizontal avoidance except for special cases. However, when the sampling points are symmetric or when more than three aircraft are involved, the procedure is not adequate and some provisions are needed. to this end, the sampling point arrangement in the initial stage before the avoidance pattern is formed and the three-dimensional avoidance including vertical avoidance can be considered.
---
paper_title: A real-time monocular vision-based frontal obstacle detection and avoidance for low cost UAVs in GPS denied environment

paper_content:

This paper presents a novel monocular vision-based realtime obstacle detection and avoidance for a low cost unmanned aerial vehicle (UAV) in an unstructured, GPS denied environment. We propose a mathematical model to estimate the relative distance from the UAV's camera to an obstacle which will subsequently be used in a collision avoidance algorithm. We validate our model with some real time experiments under both stationary and dynamic motion of the UAV during its flight. The results show good agreement with the ground truth values with an acceptable percentage of error in estimation under 3% thus proving it can facilitate obstacle detection and avoidance for low cost and lightweight UAVs.
---
paper_title: Reactive Collision Avoidance for Unmanned Aerial Vehicles Using Doppler Radar

paper_content:

Research into reactive collision avoidance for unmanned aerial vehicles has been conducted on unmanned terrestrial and mini aerial vehicles utilising active Doppler radar obstacle detection sensors. Flight tests conducted by flying a mini UAV at an obstacle have confirmed that a simple reactive collision avoidance algorithm enables aerial vehicles to autonomously avoid obstacles. This builds upon simulation work and results obtained using a terrestrial vehicle that had already confirmed that active sensors and a reactive collision avoidance algorithm are able to successfully find a collision free path through an obstacle field.
---

Title: A Survey on Unmanned Aerial Vehicle Collision Avoidance Systems

Section 1: Introduction
Description 1: Introduce the significance of UAVs, highlight the necessity for collision avoidance systems, and provide a brief overview of existing surveys and the current paper's contributions.

Section 2: Overview and key concepts of collision avoidance systems
Description 2: Explain the main functions of CAS for UAVs, the essential problems a CAS must address, and introduce the components of a CAS: sensing and detection, and collision avoidance/maneuver approach.

Section 3: Other design factors
Description 3: Discuss additional design factors relevant to CAS such as sensing dimensions, types of obstacles considered, and types of UAVs.

Section 4: Sensors and means of sensing
Description 4: Detail the various sensors and sensing methods employed in CASs, including ADS-B, visual sensors, radar, cooperative UAV information sharing, and assumed working sensors.

Section 5: Collision detection
Description 5: Describe different approaches for collision detection including trajectory calculation, worst case, probabilistic, and act as seen methods.

Section 6: Collision avoidance/maneuver approach
Description 6: Present the strategies used to avoid collision once detection occurs, categorized into geometric, optimized trajectory, bearing angle based, force field, and other approaches.

Section 7: Geometric approach
Description 7: Explain how collisions are determined and avoided using geometric methods, often involving trajectory simulation.

Section 8: Optimized trajectory approach
Description 8: Describe the generation of optimized trajectories that ensure collision avoidance while maintaining a predetermined path.

Section 9: Bearing angle based approach
Description 9: Introduce approaches that utilize visual sensors to keep obstacle images at safe positions, preventing collision.

Section 10: Force field approach
Description 10: Discuss the use of potential fields to generate collision-free trajectories, based on principles akin to repulsive and attractive electrical fields.

Section 11: Other types
Description 11: Cover additional unique approaches to collision avoidance, such as using radar sensor methods, probabilistic methods, and combined sensors and geometrical calculations.

Section 12: Conclusion
Description 12: Summarize the survey, reiterate the key aspects of various CAS components and approaches, and discuss their advantages and disadvantages.