Swarm Optimization Approach for Light Source Detection by Multi-robot System - Hoang, Anh Quy (ĐHQGHN, 2017)
Exploration and searching in unknown or hazardous environments using multi-robot systems (MRS) is among the principal topics in robotics. There have been numerous works on searching and detection of odor, fire or pollution sources. In this paper, a modified Particle Swarm Optimization Algorithm (PSO) was presented for MRS on detecting light sources, namely APSO. In the proposed algorithm, an integration of conventional PSO and Artificial Potential Field (APF) is employed to use swarm intelligence for space exploration and light source detection. The formulas for APSO velocities are based on those of PSO and APF. Furthermore, each particle is surrounded by an APF that forms repulsive force to prevent collision while the swarm is in operation.The simulation results of APSO in Matlab by various scenarios confirmed the reliability and efficiency of the proposed algorithm.