Research on Search Algorithm by PSO with Virtual Pheromone and Dynamical Niche for Swarm Robots

Abstract

This paper proposes a search algorithm by using particle swarm optimization (PSO) with virtual pheromone and a dynamical niche for swarm robots. Swarm robots are attracting attention in the disaster area to search for victims. The search algorithm is a combination of global search and local search. PSO with virtual pheromone is one of the unified control rules which achieve global search and local search. By using virtual pheromone, it is possible to recognize the unsearched area. This paper focuses on the global search for efficient search. For the efficient search, it is necessary for swarm robots to be divide into small groups dynamically due to the unresearched area. Therefore, this paper proposes the dynamic niche method by PSO with the virtual pheromone. By using the proposed method, the swarm robots detected the multiple unsearched areas and diatonically are divided them into several groups. From the simulation results, the validity of the proposed method was confirmed.