关键词: 蚁群优化, 遗传算法, 移动机器人, 路径规划, 信息素

Abstract: In order to overcome the limitation of the current path planning algorithms for mobile robot, a fusion algorithm based on ant colony optimization and genetic optimization was proposed. First, this method used pheromone update and path node selection technology to find optimization paths quickly so as to form initial population, and the ant executed a local search again once the robot went forward and dealt with random obstacles. Second, it optimized the individuals of the population by using Genetic Algorithm (GA) in the global scope, which could make the robot move on a globally optimal path to the ending node. The simulation results indicate the feasibility and effectiveness of the proposed method.

Key words: Ant Colony Optimization (ACO), Genetic Algorithm (GA), mobile robot, path planning, pheromone