Abstract

Recently, more and more researches have been conducted on the multi-robot system by applying bio- inspired algorithms. Particle Swarm Optimization (PSO) is one of the optimization algorithms that model a set of solutions as a swarm of particles that spread in the search space. This algorithm has solved many optimization problems, but has a defect when it is applied on search tasking. As the time progress, the global searching of PSO decreased and it converged on a small region and cannot search the other region, which is causing the premature convergence problem. In this study we have presented a simulated multi-robot search system to overcome the premature convergence problem. Experimental results show that the proposed algorithm has better performance rather than the basic PSO algorithm on the searching task.

Keywords:

Multi-robot search system, particle swarm optimization, premature convergence problem,

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Competing interests

The authors have no competing interests.

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