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Optimal cooperative collision avoidance between multiple robots based on Bernstein–Bézier curves

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Bibliographic Details
Title: Optimal cooperative collision avoidance between multiple robots based on Bernstein–Bézier curves
Authors: Škrjanc, Igor1, Klančar, Gregor gregor.klancar@fe.uni-lj.si
Source: Robotics & Autonomous Systems. Jan2010, Vol. 58 Issue 1, p1-9. 9p.
Subjects: Cooperative processing, Mobile robots, Curves, Acceleration (Mechanics), Mathematical models, Nonholonomic dynamical systems
Abstract: Abstract: In this paper a new cooperative collision-avoidance method for multiple, nonholonomic robots based on Bernstein–Bézier curves is presented. The main contribution focuses on an optimal, cooperative, collision avoidance for a multi-robot system where the velocities and accelerations of the mobile robots are constrained and the start and the goal velocity are defined for each robot. The optimal path of each robot, from the start pose to the goal pose, is obtained by minimizing the penalty function, which takes into account the sum of all the path lengths subjected to the distances between the robots, which should be larger than the minimum distance defined as the safety distance, and subjected to the velocities and accelerations, which should be lower than the maximum allowed for each robot. The model-predictive trajectory tracking is used to drive the robots on the obtained reference paths. The results of the path planning, real experiments and some future work ideas are discussed. [Copyright &y& Elsevier]
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Database: Engineering Source
Description
Abstract:Abstract: In this paper a new cooperative collision-avoidance method for multiple, nonholonomic robots based on Bernstein–Bézier curves is presented. The main contribution focuses on an optimal, cooperative, collision avoidance for a multi-robot system where the velocities and accelerations of the mobile robots are constrained and the start and the goal velocity are defined for each robot. The optimal path of each robot, from the start pose to the goal pose, is obtained by minimizing the penalty function, which takes into account the sum of all the path lengths subjected to the distances between the robots, which should be larger than the minimum distance defined as the safety distance, and subjected to the velocities and accelerations, which should be lower than the maximum allowed for each robot. The model-predictive trajectory tracking is used to drive the robots on the obtained reference paths. The results of the path planning, real experiments and some future work ideas are discussed. [Copyright &y& Elsevier]
ISSN:09218890
DOI:10.1016/j.robot.2009.09.003