现代电子技术2026，Vol.49Issue(18)：174-179,6.DOI:10.16652/j.issn.1004-373X.2026.18.027
阈值引导树优化的RRT*机械臂路径规划算法研究
Research on RRT* manipulator path planning algorithm optimized by threshold-guided tree
摘要
Abstract
In allusion to the problems of strong randomness,poor guidance,and low sampling efficiency in the traditional rapidly-exploring random tree(RRT)algorithm,an improved RRT* algorithm based on threshold-guided tree is proposed.In this algorithm,node values are evaluated to filter out high-value nodes,and the directional growth of the random tree is implemented by combining with dynamic threshold iteration,so as to reduce the search randomness.In order to prevent getting stuck in local exploration deadlocks,a lightweight restart mechanism is introduced.An adaptive sampling strategy is used to efficiently allocate sampling resources and enhance the goal-oriented nature of sampling.A direct connection strategy is introduced to accelerate the algorithm convergence.The cubic B-spline smoothing on the generated path is conducted.The improved RRT* algorithm is compared with related algorithms.The simulation experimental results show that the improved RRT* algorithm is improved in terms of path length,number of path nodes,number of iterations and node utilization,verifying the feasibility and effectiveness of the improved algorithm.关键词
机械臂/路径规划/改进RRT*算法/阈值引导树/节点筛选/自适应采样Key words
manipulator/path planning/improved RRT* algorithm/threshold-guided tree/node filtering/adaptive sampling分类
信息技术与安全科学引用本文复制引用
杨梓轩,徐海黎,李靖,蔡嘉俊,邢强,沈标..阈值引导树优化的RRT*机械臂路径规划算法研究[J].现代电子技术,2026,49(18):174-179,6.基金项目
南通市自然科学基金(JC2023062) （JC2023062）
