摘要
本文提出了基于改进蚁群算法的移动机器人动态路径规划方法.首先针对蚁群算法收敛速度慢,容易陷入局部最优的缺点,提出了根据目标点自适应调整启发函数,提高算法的收敛速度;借鉴狼群分配原则对信息素进行更新,避免搜索陷入局部最优.其次为了优化改进蚁群算法的性能,提出用粒子群算法对改进蚁群算法的重要参数进行优化选择.最后实现了基于改进蚁群算法的移动机器人动态路径规划并完成了仿真实验,实验结果证明了该方法的可行性和有效性.
The dynamic path planning for mobile robot based on improved ant colony optimization algorithm is presented.Firstly,to increase the convergence speed,the heuristic function modified adaptively according to the target point is proposed.To avoid the local optimum,the rule updating the pheromone based on the assignment rule of wolf colony is proposed.Secondly,to optimize the performance of the improved ant colony,the important parameters of the improved ant colony optimization algorithm are optimized by the particle swarm optimization.Finally,the dynamic path planning for mobile robot based on improved ant colony optimization algorithm is implemented and the simulation experiments are finished.From the results,it can see that the dynamic path planning method is viable and efficient.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2011年第5期1220-1224,共5页
Acta Electronica Sinica
基金
国家自然科学基金(No.60775058)
教育部科学技术研究重点项目基金(No.107028)
中央高校基本科研业务费专项基金(No.108G07)
关键词
移动机器人
路径规划
改进蚁群算法
mobile robot
path planning
improved ant colony optimization algorithm
