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A distributed swarm intelligence based algorithm for a cooperative multi-robot construction task

机译:一种合作多机器人施工任务的分布式群智能算法

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A collective construction task require a multi-robot system to search for randomly distributed building blocks and push those blocks to some predefined locations. To address this problem, a bio-inspired swarm intelligence based algorithm is proposed for a distributed multi-robot system to combine explorative searching and dynamic task allocation together for collective construction. Basically, a virtual pheromone trail based method is proposed as the message passing mechanism among the robots, where robots make distributed movement decisions through local interactions. Since blocks may need multiple robots to work together, dynamic task allocation among robots is necessary. A modified Particle Swarm Optimization (PSO) method is proposed to balance the exploration and exploitation, which helps to allocate reasonable robots to different target blocks. The simulation results in multi-robot construction task demonstrate the efficiency and robustness of the proposed method.
机译:集体施工任务需要多机器人系统来搜索随机分布的构建块,并将这些块推到一些预定义位置。为了解决这个问题,提出了一种用于分布式多机器人系统的生物启发群智能算法,以将探索性搜索和动态任务分配组合在一起进行集体结构。基本上,建议虚拟信息素轨迹的方法作为机器人之间的消息传递机制,其中机器人通过局部交互使分布式运动决策。由于块可能需要多个机器人工作,因此机器人之间的动态任务分配是必要的。建议修改的粒子群优化(PSO)方法平衡勘探和剥削,这有助于将合理的机器人分配给不同的目标块。多机器人施工任务的仿真结果展示了所提出的方法的效率和鲁棒性。

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