基于一种蚁群算法的多机器人动态感知任务分配

Multi-robot Dynamically Perceived Task Allocation Based on an Ant Colony Algorithm

  • 摘要: 多机器人系统在具有任务聚集特征的动态感知任务环境下执行搜集任务时,存在着由于任务分配不当而引起的冲突加剧问题.针对这一问题,提出了一种基于排斥信息素型蚁群算法的多机器人任务自主分配方法.进行了未知非结构化环境下的多机器人协作搜集仿真实验.仿真结果表明,采用本文所提方法可以实现多机器人搜集任务的自主分配,有效减少机器人的空间冲突,尤其在机器人数量较多的情况下,更能显示出该方法的优势.

     

    Abstract: In the dynamically perceived task environment with task-rich area,multi-robot foraging faces a lot of spatial conflictions caused by improper task allocation.In order to solve this problem,an autonomous task allocation method,which is based on an ant colony algorithm named repulsive pheromone ant colony algorithm(PR-ACA),is presented for the multi-robot system.Under the unknown unstructured environment,a simulation experiment of multi-robot cooperative foraging is performed.Experiment results show that the presented method can make multiple robots perform task allocation autonomously,and can effectively decrease spatial confliction among robots,especially when the group size is large.

     

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