An improved capturing algorithm based on particle swarm optimization for swarm robots system

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Shi, Zhiguo
Zhang, Xiaomeng
Tu, Jun
Liui, Lei
Wei, Junming

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In recent years, the number of researches in which swarm intelligence shown by individual communication in swarm robots is increasing. As one of the representative algorithms in swarm intelligence, particle swarm optimization has been applied to many fields because of its simple concept, easy realizing and good optimization characteristics. However, it still has some disadvantages such as easy falling in the local best situation and solving the discrete optimization problems poor. In this paper, a swarm-robot capturing algorithm which is based on particle swarm optimization and assimilates outstanding advantages of fruit fly algorithm is proposed. Robots in the simulation environment complete the task that rescuing the victim with the algorithm in a disaster. The simulation in Player/Stage shows that the algorithm can make up the disadvantages of particle swarm optimization and complete the capturing well at the same time.

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CSAE Proceedings, 2012 IEEE International Conference on Computer Science and Automation Engineering

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2037-12-31