动态环境下可扩展移动机器人群体的围捕控制

Pursuit Control of Scalable Swarm System of Mobile Robots in Dynamic Environment

  • 摘要: 针对协作追逃问题的环境受限以及围捕者与目标的速度比率受限问题,提出了一种规模可扩展的机器人群体围捕移动目标的切换式策略,该策略可有效完成动态环境中目标机器人速度无约束的围捕任务,即围捕机器人通过数目优势进行协作围捕来克服其速度上的劣势以完成对目标机器人的围捕.围捕过程中,考虑了面向目标机器人的虚拟势点子行为以及与邻居个体的位姿匹配行为(编队子行为),在距离目标较远时位姿匹配子行为权值大于虚拟势点子行为权值,而距离目标较近时则以虚拟势点子行为为主.仿真实验证明了所提解决方案的可行性和有效性.

     

    Abstract: Facing the problems of the constrained environment and the constrained velocity ratio between pursuers and evader in collaborated pursuit-evasion games,a "switch" type strategy for scalable swarm of robots to pursue a mobile goal is proposed,in which the swarm is able to finish effectively the pursuit task in dynamic environment while the velocity of the target robot is unconstrained,i.e.,the pursuit robots hunt the target robot in collaboration and with the predominance of numbers to overcome their velocity weakness.In the process of pursuit,the following two behaviors are considered: the moving toward "suppositional potential point" sub-behavior that is task-robot-oriented and the posture matching with neighbor agents(formation).When the distance to goal is farther,the behavior of posture matching is mainly considered,whereas when it is closer,moving toward suppositional potential point is mainly taken into account.Simulated experiments show that the proposed scheme is feasible and effective.

     

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