Optimal Path Planning of Mobile Robots: A Comparison Study

Abstract

Recently, mobile robotics is increasingly becoming responsive to many areas including agriculture, health, nanotechnology, nuclear technologies and the military. The sensitive aspect of these applications requires collision - free path planning performances of the mobile robot. Since path planning is treated as an optimization problem, we provide in this paper, a comparison study between two path planning approaches with obstacles avoidance: A classic method is addressed by the deterministic Levenberg Marquardt (LM) optimization technique and an evolutionary one is presented by the heuristic Particle Swarm Optimization (PSO) technique. Simulation results show main advantages and drawbacks of each approaches. Hence, PSO has been demonstrated to be more efficient and useful especially in dynamic navigation environments.