基于改进蚁群算法的移动机器人路径规划

Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm

针对蚁群算法应用于机器人路径规划存在的全局搜索能力差、初始化信息素少、收敛性差、寻优能力弱等问题,提出了一种多因素改进的蚁群算法。通过改变初始化信息素浓度分配、改变启发式函数、采取蚂蚁回退策略、引入蚂蚁优化排序等方法对蚁群算法进行优化。利用MATLAB软件对改进蚁群算法进行仿真和六足机器人实验。结果表明:改进后的算法在路径更优,迭代次数更少,提高了算法的鲁棒性和寻优能力。

Aiming at the problems of poor global search ability,low initialization pheromone,poor convergence,and weak optimization ability when ant colony algorithm was applied to robot path planning,a multi-factor improved ant colony algorithm was proposed.The ant colony algorithm was optimized by changing the distribution of the initial pheromone concentration,changing the heuristic function,adopting the ant regression strategy,and introducing the ant optimization sorting method.Using MATLAB software to simulate the improved ant colony algorithm and hexapod robot experiments.The results show that the improved algorithm has better path and fewer iterations,which improves the robustness and optimization ability of the algorithm.