A PSO-Based Global Path Planning Approach for Mobile Robots

Abstract

In this paper, a PSO-based global path planning approach is proposed for mobile robots operating in environments highly cluttered with static obstacles and danger zones. Firstly, by suitably representing the workspace environment and the candidate robot path solutions, the path planning task is formulated as a bi-objective optimization problem that includes path length and collision degree objective functions. Then, the weighted sum method is used to reformulate the bi-objective optimization task as a single one. Moreover, to obtain better mobile robot paths in terms of path length and collision degree parameters, the meta-heuristic PSO algorithm is applied to solve the formulated path planning optimization task. Finally, various numerical tests of highly cluttered robot workspace environments have been conducted to assess the performance of the proposed global path planner algorithm.