信息与控制2025，Vol.54Issue(6)：893-905,13.DOI:10.13976/j.cnki.xk.2024.3351
基于采样区域限制RRT的机械臂路径规划算法
RRT Path Planning Algorithm Based on Sampling Area Restriction for Manipulator
摘要
Abstract
To address the issues of excessive sampling randomness,low search efficiency,and zigzag-ging in traditional rapidly-exploring random tree(RRT)algorithms for robot path planning,we propose an improved RRT algorithm with a sampling area restriction strategy(SAR-RRT).First,to mitigate excessive randomness,we enhance the target orientation of the random tree by introducing a target bias strategy.And we constrain sampling using a spherical sampling region and an angular restriction strategy,which limits exploration in unnecessary spatial regions.Second,to improve search efficiency,we adaptively optimize the node expansion of the random tree.A multi-step expansion strategy is employed to maximize the use of environmental and obstacle information,while a greedy approach accelerates tree convergence,reducing path generation time.Finally,we apply secondary optimization to the initial planned path.After removing redundant points,we smooth the path using a cubic B-spline curve,improving overall path quality.Experi-mental results demonstrate that the SAR-RRT algorithm completes path-planning tasks in 2D and 3D scenarios.Compared with the traditional RRT algorithm,the proposed method reduces path length by 27.73％,planning time by 85.25％,and sampling points by 87.19％while generating a smoother path.关键词
快速拓展随机树算法/路径规划/目标偏置/采样区域限制/B样条曲线Key words
RRT(Rapidly-exploring Random Tree)algorithm/path planning/target bias/sampling area restriction/B-spline curve分类
信息技术与安全科学引用本文复制引用
何波,李虓,徐胜军,刘光辉..基于采样区域限制RRT的机械臂路径规划算法[J].信息与控制,2025,54(6):893-905,13.基金项目
国家自然科学基金面上项目(62476211,52278125) （62476211,52278125）
陕西省自然科学基础研究计划(2022JQ-681,2023-JC-YB-532,2024JC-YBMS-483) （2022JQ-681,2023-JC-YB-532,2024JC-YBMS-483）
陕西省科技厅社发攻关项目(2021SF-429) （2021SF-429）
