三维环境中机器人路径规划算法改进
Improvement of robot path planning algorithm in 3D environment
杨小月 1李宏伟 2秦雨露 1姜懿芮 1王步云2
作者信息
- 1. 郑州大学 计算机与人工智能学院,河南 郑州 450001
- 2. 郑州大学 地球科学与技术学院,河南 郑州 450001
- 折叠
摘要
为解决快速扩展随机树算法(rapid-exploration random tree,RRT*)在三维环境中盲目搜索路径以及缺乏节点扩展记忆性等问题,提出一种融合蚁群算法的双向搜索算法ACO-RRT*.为适应精细化三维建模环境和解决地面起伏不平坦等问题,对RRT*算法进行改进优化.采用双向搜索策略,在起点和终点同时运行改进后的RRT*算法和蚁群算法,相向而行,对路径长度和运行时间进行优化.针对生成路径不够平滑等问题,引入B样条曲线平滑策略优化路径.仿真结果表明,所提算法能够有效用于机器人三维路径规划.
Abstract
To solve the problems such as blind search path in 3D environment and lack of node expansion memory of rapid expan-sion random tree(RRT*)algorithm,a bidirectional search algorithm ACO-RRT*,in which the ant colony algorithm was com-bined,was proposed.To adapt to the refined 3D modeling environment and solve the problems such as uneven ground,the RRT*algorithm was improved and optimized.The improved RRT*algorithm and the ant colony algorithm were run simulta-neously at the starting point and the end point using a two-way search strategy to optimize the path length and running time.Aiming at the problem that the generated path is not smooth enough,the B-spline smoothing strategy was introduced to optimize the path.Simulation results show that the proposed algorithm can be effectively used for robot 3D path planning.
关键词
快速扩展随机树/蚁群算法/B样条曲线/算法融合/双向搜索/机器人路径规划/三维环境Key words
rapidly exploring random tree/ant colony algorithm/B-spline curve/algorithm fusion/bi-directional search/robot path planning/3D environment引用本文复制引用
基金项目
国家自然科学基金重点基金项目(42130112)
中国工程院专题咨询研究基金项目(HENZT07)
出版年
2024
NETL
NSTL
万方数据