In a complex environment and concerning the problems of choosing parameters brought by the mixture of two multi-robot formation methods, the Leader-Follower method and a behavior-based method, this paper improved two methods and optimized five kinds of behavior parameters online to make the multi-robot formation better with the help of Particle Swarm Optimization (PSO) algorithm. The simulation results validate that the proposed algorithm is feasible and it achieves expected optimization effects.%在复杂环境下,针对Leader-Follower法和基于行为法相结合的多机器人混合编队方法配置参数难的问题,引入粒子群优化(PSO)算法,对5种行为参数进行在线优化,进而改进了传统的混合编队方法,使多机器人编队效果更优.同时通过仿真实验结果验证了所提出算法的可行性,且达到了实验预期的优化效果.
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