基于松散偏好规则的群体机器人系统自组织协作围捕

摘要

针对群体机器人协作围捕,提出了一种基于松散偏好规则的自组织方法.首先给出了个体机器人的自由运动模型和围捕行为的数学描述.通过对围捕行为的分解,构造松散偏好规则来使个体机器人在自组织运动过程中相互协调最终形成理想的围捕队形.在此基础上,设计了个体自组织运动控制器.最后运用Lyapunov稳定性定理证明系统的稳定性.仿真和实验结果表明,本文给出的自组织方法对于群体机器人协作围捕是行之有效的.%A novel self-organizing approach to cooperative hunting by swarm robotic systems is put forward based on loose-preference rule. Firstly, an individual autonomous motion planning is presented, and the cooperative hunting behaviors are mathematically described. According to decomposition of hunting behaviors, a loose-preference rule is established for the individuals to form the ideal hunting formation during the self-organizing process by the interaction between the target and individuals. Then, we employ the proposed rule to design an autonomous motion controller of the individuals. Finally, the stability of self-organizing system is analyzed by Lyapunov stability criterion. Simulations and experiments demonstrate the feasibility and effectiveness of the proposed approach to cooperative hunting by swarm robotic systems.