机械科学与技术2025，Vol.44Issue(12)：2078-2089,12.DOI:10.13433/j.cnki.1003-8728.20230383
动态约束采样RRT*-Connect算法的移动机器人路径规划
Dynamic Constrained Sampling RRT*-Connect Algorithm for Mobile Robot Path Planning
摘要
Abstract
In order to solve the problems of RRT*-Connect algorithm in complex obstacle environment,such as large randomness,low search efficiency and redundant path nodes,a path planning algorithm of mobile robot based on dynamic constrained sampling RRT*-Connect algorithm is proposed.Firstly,based on RRT*-Connect algorithm,dynamic target node probability bias is used to sample the target node of the opposite search tree,so that the target of double tree extension is the node of the opposite search tree and it reduces the randomness of the double tree connection.Combined with the dynamic region sampling method of target node,the multi-stage sampling region is constructed with the target node and the node nearest to the target node as the core,and the expansion direction of the search tree is constrained to realize dynamic constrained sampling,and the local oscillation is avoided by setting a threshold.On this basis,the repulsive force idea of artificial potential field method is introduced to design the adaptive dynamic step size based on the global and local environmental complexity coefficient,which greatly improves the search efficiency.Additionally,Cantmull-Rom spline curve was used for path smoothing.The simulation results show that the algorithm has faster convergence speed,higher efficiency,more than 30%node utilization rate,significantly reduced useless nodes,less searching branches,and can adapt to various complex obstacle environments.Compared with RRT*-Connect algorithm,the running time of the proposed algorithm is reduced by more than 23%,and the path length is reduced by more than 7%.关键词
移动机器人/动态约束采样/自适应动态步长/路径平滑Key words
mobile robot/dynamic constrained sampling/adaptive dynamic step size/path smoothing分类
信息技术与安全科学引用本文复制引用
CHEN Zhong,YIN Yanchao,YI Bin,LIN Wenqiang,HOU Buchao,SUN Yuming..动态约束采样RRT*-Connect算法的移动机器人路径规划[J].机械科学与技术,2025,44(12):2078-2089,12.基金项目
国家自然基金项目(52065033)与云南省重大科技项目(202302AD080001) （52065033）
