Comparing modified PSO algorithms for MRS in unknown environment exploration

Abstract

Multi-robot systems (MRS) have shown clear advantages over single robots in the application of exploring unknown environments - a fundamental problem in robotics. Among algorithms which are able to be applied to MRS in the application, Particle Swarm Optimization (PSO) - a heuristic optimization technique inspired by social behavior of natural swarms - has received much attention and is well-known for its efficiency and simplicity to implement. However, when conventional PSO is applied, the problems of disconnection and collision within the system are inevitable. Two of various methods proposed to address these crucial issues are applying BOIDS and Artificial Potential Field (APF) to modify PSO. In this work, we simulated both modified algorithms on Matlab under various scenarios for analysis and comparison.