基于蚁群与DWA融合的移动机器人动态路径规划
Dynamic Path Planning Method of Mobile Robot Based on Ant Colony and DWA Fusion
张晓倩 1黄磊 1石雨婷 1汪建华 1祁良剑1
作者信息
- 1. 南京林业大学机械电子工程学院,南京 210037
- 折叠
摘要
路径规划算法是移动机器人研究的关键环节,针对传统蚁群算法搜索效率慢及无法实时避障的问题,提出了将改进的蚁群算法与DWA融合的动态路径规划方法.首先,改进蚁群算法中的状态转移概率和信息素更新规则,来提高蚁群算法的搜索速度;其次,采取路径优化策略,提高全局路径的平滑度;然后,在DWA的评价函数中添加全局路径融合子函数和障碍物安全阈值来提高移动机器人的动态避障能力.仿真实验结果表明,改进算法在路径拐点次数上较传统蚁群算法提高了75%,且能够实时检测未知障碍物并成功躲避.证明改进算法在复杂的动态环境下,路径的搜索性能、平滑度及动态避障方面都有明显的改进.
Abstract
Path planning algorithm is the key link of mobile robot research.In view of the traditional ant colony algorithm search efficiency is slow and unable to real-time obstacle avoidance problem,put forward the improved ant colony algorithm with DWA fusion method of dynamic path planning Firstly,the state transition probability and pheromone updating rule are improved to improve the searching speed of ant colo-ny algorithm.Secondly,the path optimization strategy is adopted to improve the smoothness of the global path.Then the global path fusion function and the obstacle safety threshold are added to the evaluation func-tion of DWA to improve the dynamic obstacle avoidance ability of mobile robot.The simulation experiment results show that the improved algorithm on the path to the inflection point number than the traditional ant colony algorithm is improved by 75%and can real-time detect unknown obstacles and managed to escape.Proved in this paper,the proposed algorithm has obvious improvement in path searching performance,smoothness and dynamic obstacle avoidance in complex dynamic environment.
关键词
移动机器人/路径规划/蚁群算法/DWA算法/动态避障Key words
mobile robot/path planning/ant colony algorithm/DWA algorithm/dynamic obstacle avoid-ance引用本文复制引用
基金项目
国家自然科学基金项目(31901239)
2021年江苏省大学生创新训练计划项目(202110298016Z)
出版年
2024
NETL
NSTL
维普
万方数据