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A potential field-based PSO approach for cooperative target searching of multi-robots

Yifan Cai, Simon X. Yang

Year
2014
Citations
13

Abstract

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 (PPSO) 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 PPSO approach. In the simulation studies, various situations are investigated to test the flexibility and applicability of the proposed approach. In addition, the results are compared to the ones with other commonly used methods to demonstrate the advantage of the proposed method in exploration efficiency.

Keywords

RobotFlexibility (engineering)Particle swarm optimizationComputer scienceSwarm roboticsField (mathematics)Fitness functionPotential fieldMobile robotFunction (biology)

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