Collision free coordination of autonomous multiagent systems

Yu, Changbin; Fi̇dan, Barış; Shames, Iman; Sandeep, S.R.; Anderson, Brian D. O.

doi:10.23919/ecc.2007.7068971

Cited by 6 publications

(13 citation statements)

References 19 publications

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“…Here we use the Line-of-Sight Obstacle Avoidance approach of [4] to perform collision avoidance. The principle of Line-of-Sight Obstacle Avoidance is as follows: When the leader or the first follower sees an obstacle blocking the view of the target, it will go around the obstacle in order to see the target again, and then it can move towards the target, as illustrated by Fig.…”

Section: Obstacle Avoidancementioning

confidence: 99%

“…Within the robotics swarm, no information is communicated among the robots, and only passive 2-dimensional vision information is available to maintain the formation. In [1], using the inter-robot distances estimated, Shaohao a distributed control law based on earlier results in [2]- [4] is used to move the robotic swarm in formation from an arbitrary initial position to an arbitrary final position, without deforming the formation shape during motion.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Splitting/rejoining can be one solution to avoid collision with the obstacles [4], as suggested by observation of fish swarms: the swarm of fish will split into two parts, each of which goes one side of the obstacle. Another approach [3], [4] is to move the entire formation to one side of the obstacle and this is the approach we use in this paper. Different methods for moving the formation as a whole around an obstacle are introduced in [3], [4]: Line-of-Sight Obstacle Avoidance, Nearest Effective Obstacle Avoidance and Sheepdog Approach.…”

Section: Introductionmentioning

confidence: 99%

“…Another approach [3], [4] is to move the entire formation to one side of the obstacle and this is the approach we use in this paper. Different methods for moving the formation as a whole around an obstacle are introduced in [3], [4]: Line-of-Sight Obstacle Avoidance, Nearest Effective Obstacle Avoidance and Sheepdog Approach. Among these, we use Line-of-Sight Obstacle Avoidance in this paper, mainly because the principles of this approach fit well in vision based formation control implementation.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Single view depth estimation based formation control of robotic swarms: Obstacle avoidance, simulation, and practical issues

Zhai

Fi̇dan

Öztürk³

et al. 2008

2008 16th Mediterranean Conference on Control and Automation

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Abstract-In a companion paper we have presented a practical formation motion control scheme for robotic swarms based on single view depth estimation. In this paper we adapt this control scheme to the cases where there are obstacles to be avoided in the region of interest. First, a set of distributed control laws for the agents, to be incorporated with depth (distance) estimation scheme, are introduced to move the formation from an arbitrary initial position to an arbitrary final position without deforming the formation shape or having a collision with an obstacle. Then, we present simulation results on formation control using the proposed control scheme for both obstacle free and with obstacle cases. We later discuss certain practical issues regarding the proposed scheme. The robots do not have any global positioning sensors, and they do not communicate with each other. The performance of the overall system as well as the effects of delay and quantization in estimation of distance are analyzed via simulations.

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Section: Obstacle Avoidancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Single view depth estimation based formation control of robotic swarms: Obstacle avoidance, simulation, and practical issues

Zhai

Fi̇dan

Öztürk³

et al. 2008

2008 16th Mediterranean Conference on Control and Automation

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View full text Add to dashboard Cite

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Safe Autonomous Agent Formation Operations Via Obstacle Collision Avoidance

Deghat¹,

Shames²,

Anderson³

2014

Asian Journal of Control

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In this paper, we consider the problem of flocking and shape-orientation control of multi-agent systems with inter-agent and obstacle collision avoidance. We first consider the problem of forcing a set of autonomous agents to form a desired formation shape and orientation while avoiding inter-agent collision and collision with convex obstacles, and following a trajectory known to only one of the agents, namely the leader of the formation. Then we build upon the solution given to this problem and solve the problem of guaranteeing obstacle collision avoidance by changing the size and the orientation of the formation. Changing the size and the orientation of the formation is helpful when the agents want to go through a narrow passage while the existing size or orientation of the formation does not allow this. We also propose collision avoidance algorithms that temporarily change the shape of the formation to avoid collision with stationary or moving nonconvex obstacles. Simulation results are presented to show the performance of the proposed control laws.

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Close target reconnaissance with guaranteed collision avoidance

Shames

Fi̇dan

Anderson

2010

Intl J Robust & Nonlinear

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SUMMARYThis manuscript considers the problem of close target reconnaissance by a group of autonomous agents. The overall close target reconnaissance (CTR) involves subtasks of avoiding inter-agent collisions, reaching a close vicinity of a specific target position, and forming an equilateral polygon formation around the target. The agents performing the task fly at a constant speed to mimic the velocity behavior of small fixed-wing unmanned aerial vehicles (UAV). A decentralized control scheme is developed for this overall task and the finite-time convergence of the system under the proposed control law is established. Furthermore, it is guaranteed that no collision occurs among the agent. The relevant analysis and simulation test results are provided.

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Collision free coordination of autonomous multiagent systems

Cited by 6 publications

References 19 publications

Single view depth estimation based formation control of robotic swarms: Obstacle avoidance, simulation, and practical issues

Single view depth estimation based formation control of robotic swarms: Obstacle avoidance, simulation, and practical issues

Safe Autonomous Agent Formation Operations Via Obstacle Collision Avoidance

Close target reconnaissance with guaranteed collision avoidance

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