Gas Source Localization using Grey Wolf Optimizer

Gas source localization is an ability which has yet to be successfully implemented in synthetic systems although it is widely exhibited by various organisms. Although single robot implementation has been explored, it is still prone to single point failures and is limited in sporadic gas dispersion conditions. Swarm intelligence based algorithms such as Particle Swarm Optimization and Ant Colony Optimization has shown the feasibility and advantage of using multi-robot strategy for gas source localization. This paper explores Grey Wolf Optimizer (GWO) as an alternative algorithm for gas source localization. It was found that, although some GWO search behavior is favorable for gas source localization, the algorithm may fail when used with low numbers of robots. The algorithm was able to localize the peak gas concentration in approximately 30 minutes. The best success rate is found to be 72% with 7 searcher robots