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A probability particle swarm optimizer with information-sharing mechanism for odor source localization
This paper deals with the problem of odor source localization using a multi-robot system. Taking limited communication networks among the multi-robot system into account, a new cooperative search algorithm, namely, a probability particle swarm optimizer with information-sharing mechanism, is proposed and independently executed by each robot, by which the team of robots can be efficiently coordinated to locate a stationary odor source. In order to develop the proposed algorithm, an information-sharing matrix, which is used to store information by learning from the position information of robots, is designed. Based on the matrix, the probable position of the odor source as the new position of the robot is produced by following three simple steps. Finally, the effectiveness of the proposed algorithm is illustrated in the problem of odor source localization.