Yifan Cai and Simon X. Yang
Multi-robot cooperation, PSO, artificial potential field, target searching
Multi-robot cooperation receives increasing attention. Collaboration among the robots can improve the efficiency and effectiveness for some complex tasks. Target searching in completely unknown environments is a challenging topic for multi-robot cooperation. In this paper, a novel potential field-based particle swarm optimization (PSO) approach is proposed for a team of mobile robots to cooperatively search targets in unknown environments. The potential field function is the fitness function of the PSO, which is used to evaluate the exploration priority of the unknown area. The proper cooperation rules for the multi-robot system are defined in the proposed PSO approach. The target locations are unknown, where the robots explore the area and find the targets in a reasonable and effective way. In the simulation studies, various situations with variable numbers of robots and targets are investigated. In addition, scenarios with obstacles and failing robots are considered. The results demonstrate that the proposed approach can effectively lead the multi-robot system to accomplish the target searching tasks in completely unknown environments.
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