基于学习机制蚁群算法的移动机器人路径规划
Path planning of mobile robot based on learning mechanism ant colony algorithm
唐宏伟 1罗佳强 1邓嘉鑫 1王军权 1石书琪1
作者信息
- 1. 邵阳学院多电源地区电网运行与控制湖南省重点实验室,邵阳 422000
- 折叠
摘要
针对U型障碍物环境中移动机器人路径规划问题,提出了一种学习机制蚁群算法.首先,为解决算法运行时间长的问题,引入邻域剔除,舍弃较差和对称路径;其次,为解决收敛速度慢的问题,运用禁忌策略,使蚂蚁快速逃离U型障碍物;然后,为解决路径死锁的问题,提出学习机制,不断舍弃死锁路径;最后,将该算法与其他改进算法进行仿真对比,结果表明学习机制蚁群算法相比对照组算法不仅缩短了运行时间,还提升了收敛速度,验证了该算法的优越性.
Abstract
A learning mechanism ant colony algorithm was proposed for the path planning problem of mobile robot in U-shaped obstacle environment.Firstly,to solve the problem of long algorithm running time,neighborhood removal was introduced to discard poor and symmetric paths.Secondly,to solve the problem of slow convergence speed,taboo strategies were applied to enable ants to quickly escape U-shaped obstacles.Then,to solve the problem of path deadlock,a learning mechanism was proposed to continu-ously discard deadlocked paths.Finally,a simulation comparison was conducted between the proposed algorithm and other im-proved algorithms.The results showed that the learning mechanism ant colony algorithm not only shortened the running time com-pared to the control group algorithm,but also improved the convergence speed,which verifies superiority of the algorithm.
关键词
路径规划/蚁群算法/邻域剔除/学习机制/移动机器人/U型障碍物Key words
path planning/ant colony algorithm/neighborhood removal/learning mechanism/mobile robot/U-shaped obstacle引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据