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Dynamic path planning strategy based on improved RRT^(*)algorithm 被引量:2

基于改进RRT^(*)算法的动态路径规划策略
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摘要 In order to solve the problem of path planning of mobile robots in a dynamic environment,an improved rapidly-exploring random tree^(*)(RRT^(*))algorithm is proposed in this paper.First,the target bias sampling is introduced to reduce the randomness of the RRT^(*)algorithm,and then the initial path planning is carried out in a static environment.Secondly,apply the path in a dynamic environment,and use the initially planned path as the path cache.When a new obstacle appears in the path,the invalid path is clipped and the path is replanned.At this time,there is a certain probability to select the point in the path cache as the new node,so that the new path maintains the trend of the original path to a greater extent.Finally,MATLAB is used to carry out simulation experiments for the initial planning and replanning algorithms,respectively.More specifically,compared with the original RRT^(*)algorithm,the simulation results show that the number of nodes used by the new improved algorithm is reduced by 43.19%on average.
作者 SUO Chao HE Lile 索超;贺利乐(西安建筑科技大学机电工程学院,陕西西安710055)
出处 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2022年第2期198-208,共11页 测试科学与仪器(英文版)
基金 National Natural Science Foundation of China(No.61903291)。
关键词 mobile robot path planning rapidly-exploring random tree^(*)(RRT^(*))algorithm dynamic environment target bias sampling 移动机器人 路径规划 RRT^(*)算法 动态环境 目标偏置采样
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