摘要
近年来,路径规划作为移动机器人技术研究中的一个重要领域而备受关注。针对传统蚁群算法搜索容易陷入局部最优和对动态环境适应性差的缺陷,使用狼群分配原则改进信息素的更新方式,同时在蚁群算法的基础上加入局部信息搜索策略和两步可行域搜索策略,规划出局部区域内的最优路径,直到找到最优全局目标点。将改进后的算法应用于动态路径规划,仿真结果表明:改进蚁群算法能有效避开动态障碍物,并且算法运行时间得到明显缩短。
In recent years,path planning has received much attention as an important area in the research of mobile robot technology.Aiming at the defects that traditional ant colony algorithm is easy to fall into local optimum and poor adaptability to dynamic environment,the wolf group allocation principle is used to improve the pheromone update method.At the same time,local information search strategy and two-step feasible domain are added based on ant colony algorithm.Search the strategy to plan the optimal path within the local area until the optimal global target point is found.The improved algorithm is applied to dynamic path planning.The simulation results show that the improved ant colony algorithm can effectively avoid dynamic obstacles,and the running time of the algorithm is significantly shortened.
作者
梁凯
毛剑琳
Liang Kai;Mao Jianlin(Kunming University of Science and Technology Institute of Information Engineering and Automation,Kunming 650500,China)
出处
《电子测量技术》
2020年第7期56-60,共5页
Electronic Measurement Technology
关键词
蚁群算法
狼群分配原则
局部信息
两步可行域
移动机器人
ant colony algorithm
wolf group allocation principle
local information
two-step feasible domain
mobile robot
