A Novel Approach for Swarm Robotic Target Searches Based on the DPSO Algorithm

Abstract

Cooperation between individuals plays a very important role when swarm robots search for targets. In this article, we present a novel approach that is based on the distributed particle swarm optimization (DPSO) algorithm to guide swarm robots to search for targets. Both the communication limit and the communication energy consumption (CEC) of the robots are considered. In the proposed approach, robot representatives are selected to represent all of the robots to transfer data to the base stations. The initial deployment and relocation approaches of the base stations are introduced to shorten the transmission distance of the data and to improve the search performance. In addition, a dynamic swarm division method is proposed to efficiently handle cases in which there is more than one target that must be searched for simultaneously. The effectiveness of the proposed approach is verified by some experiments. Simulation results have demonstrated that the proposed approach performs well against other comparative algorithms in various cases.