Localizing odor source with multi-robot based on hybrid particle swarm optimization

Abstract

Odor source localization is a challenging task for mobile robots in the real world. A refined hybrid particle swarm optimization by combining with bacterial foraging optimization is proposed for odor source localization of a swarm of robots. In the proposed algorithm, a chemotaxis operation is integrated into particle swarm optimization to lead robots to track a plume, and an elimination-dispersal operation is adopted to prevent particles trapping in local minim. Simulation results show that the proposed method can find an odor source with higher success rate.