The problem of localizing multiple odor sources is focused on

and a method of localizing odor sources using robots based on multi-swarm particle swarm optimization(PSO)is presented in this paper.In this method

each robot is regarded as a particle

neighboring particles form a sub-swarm

and different sub-swarms are used to localize different odor sources.In order to make the whole swarm localize as many odor sources as possible

the merging strategy of similar sub-swarms and the reducing strategy of the individual fitness are incorporated into the proposed algorithm.When the environment in which these odor sources lie changes

the globally optimal solution of a sub-swarm is selected according to the relationship between the optimal solution of the sub-swarm in the current generation and that up to the previous generation.The proposed method is applied to localize odor sources in three typical static environments and one dynamic environment

and compared with five previous methods.The experimental results confirm that the proposed method can efficiently localize odor sources.