Localizing odor sources using multiple robots based on particle swarm optimization in limited communication environments

Abstract

Considering the constraint of limited communication among robots,a method of localizing odor sources using multiple robots based on particle swarm optimization is presented on the condition of abstracting each robot as a particle.Firstly,a strategy incorporating with a repulsive function is utilized to guide a robot to rapidly search for a plume.Then the range of communication among robots is estimated based on the log-distance loss model of wireless signal propagation to form a dynamic topology structure of a particle swarm and to determine the global optimum of particles.Finally,the sampling/recovery time of a sensor is incorporated to update a particle so as to trace the plume.The proposed method is applied to localize odor sources in three various scenarios and the experimental results show its effectiveness.