Localization of multiple odor sources using modified glowworm swarm optimization with collective robots

Abstract

A multi-robot cooperation strategy based on a modified glowworm swarm optimization (M-GSO) is proposed. This strategy includes global random search of self-exploration, local search based on GSO algorithm and odor source declaration. And forbidden area setting is also introduced into the iteration process to achieve localization for multiple odor sources. This mechanism can ensure robots to start searching for the next odor source after the discovery of an odor source and ensure that other robots would not re-locate this odor source. Simulation results show that the proposed M-GSO can effectively enable the robot system to search and find all the odor sources existed in the indoor environment quickly and accurately.