Application of Multi-objective Optimization Genetic Algorithm to Robot Path Planning

An improved multi-objective optimization genetic algorithm is proposed to optimize the problem of robot global path planning with multiple objectives.The random approach combined with the heuristic method based on domain knowledge are employed in the initialization to motivate the convergence speed and three genetic operators named deletion,repair and smooth are adopted to improve the searching efficiency of the algorithm.In the selection operator,a strategy that avoids the appearance of the same individuals in the archive is incorporated to prevent premature.Simulation results indicate that the proposed algorithm can find a set of approximate Pareto optimal solutions efficiently in one run.