Global path planning approach based on ant colony optimization algorithm

来源期刊：中南大学学报(英文版)2006年第6期

论文作者：文志强 蔡自兴

文章页码：707 - 712

Key words：mobile robot;ant colony optimization;global path planning; pheromone

Abstract: Ant colony optimization(ACO)algorithm was modified to optimize the global path.In order to simulate the real ant colonies,according to the foraging behavior of ant colonies and the characteristic of food,conceptions of neighboring area and smell area were presented.The former can ensure the diversity of paths and the latter ensures that each ant can reach the goal.Then the whole path was divided into three parts and ACO was used to search the second part path.When the three parts pathes were adjusted, the final path was found.The valid path and invalid path were defined to ensure the path valid.Finally,the strategies of the pheromone search were applied to search the optimum path.However,when only the pheromone was used to search the optimum path,ACO converges easily.In order to avoid this premature convergence,combining pheromone search and random search,a hybrid ant colony algorithm(HACO)was used to find the optimum path.The comparison between ACO and HACO shows that HACO can be used to find the shortest path.