Optimum Path Planning for Mobile Robots Based on a Hybrid Genetic Algorithm

Abstract

A hybrid genetic algorithm based optimum path planning approach for mobile robots is proposed in this paper. A new proposed self-adaptive algorithm for controlling the crossover and mutation probabilities is adopted to replace the adjustment algorithm in an improved genetic algorithm, which is specifically designed for optimum path planning of mobile robots. The simulation studies in varying environments are carried out to demonstrate the effectiveness of the proposed algorithm and the simulation results show that the hybrid genetic algorithm has provided faster search speed compared with the recently reported method.