基于改进蚁群算法的机器人路径规划问题研究

Research on Robot Path Planning Problem Based on Improved Ant Colony Algorithm

针对基本蚁群算法前期搜索效率低下以及在寻优的过程中会穿过障碍物等问题,提出改进的蚁群算法,即采用动态调整启发因子、信息素初始化改进策略、可选节点的筛选机制方案进行改进工作。通过对基本蚁群算法和改进蚁群算法的仿真结果分析可知,改进后算法的最优路径长度虽然有所增加,但减少了蚂蚁前期到达最优路径的迭代次数,得到一条无碰撞、没有穿过障碍物的路径,且耗时与基本蚁群算法相持平,保证了机器人路径的安全性,提高了算法的前期搜索效率。

Aiming at the low efficiency of the basic ant colony algorithm in the early stage and the obstacles in the process of optimization,an improved ant colony algorithm was proposed,which adopts dynamic adjustment heuristic factor,pheromone initialization improvement strategy and optional node screening mechanism.By analyzing the simulation results of the basic ant colony algorithm and the improved ant colony algorithm,the optimal path length of the improved algorithm is increased,but the number of iterations of the ant reaching the optimal path is reduced.A path without collision and obstacles is obtained,and the time consumption is equal to that of the basic ant colony algorithm,which ensures the safety of the robot path and improves the early search efficiency of the algorithm.