This paper studies the problem of odor source localization in noise environment

and proposes a cooperative search method of multi-robot based on particle swarm optimization.In this method

a robot is defined as a particle

odor concentration detected by sensors of this robot is regarded as the fitness of this particle

and all robots form the swarm of PSO.Using an improved bare-bones PSO to lead the particles search cooperatively odor source

a dynamical statistic method is proposed to estimate noise degree of odor concentration detected by sensors;a probability domination relationship suitable to interval fitness is defined to compare particles and update the local leaders of particles.Moreover

a Gauss sampling method based on the global and local leaders is used to update the positions of particles.Finally

the proposed method is applied to two scenarios with odor sources

and experimental results confirmed its effectiveness on solving the problem of odor source localization in noise environment.