计算机科学与探索2024，Vol.18Issue(9)：2407-2421,15.DOI:10.3778/j.issn.1673-9418.2312047
目标区域引导的RRT*机械臂路径规划算法
Target Area Guided Manipulator Path Planning of RRT*
摘要
Abstract
A target area guided RRT*robotic arm path planning algorithm(TA-RRT*)is proposed to address the is-sues of low planning efficiency,poor path quality,and improper robotic arm pose in the traditional RRT*algorithm for robotic arm path planning.Firstly,with the traditional RRT*algorithm as the foundation,a target bias strategy is introduced and a spherical subset constraint sampling is utilized to narrow the sampling range and guide the expansion of the new node towards the target point,enhancing target orientation.By employing a direct connection strategy for new nodes,the algorithm is enabled to converge faster and the speed of path generation is improved.Secondly,by removing redundant points from the initial planning path and transforming it into a smooth path using a cubic B-spline curve,the quality of the path is improved.Finally,the position of the robotic arm is constrained.The reachability of the robotic arm linkage pose is ultimately determined through the inverse kinematics of the robotic arm,and the envelope box model is used to determine whether the robotic arm is collided with obstacles.Experimental results show that the TA-RRT*algorithm outperforms the RRT* algorithm in terms of sampling frequency,planning time,path length,and smoothness in 2D and 3D scenes,verifying the correctness and feasibility of this method.Both the robotic arm simulation experiments and the test results in real environment demonstrate that when adding pose constraints to the planned trajectory of the robotic arm during operation,the joints of the robotic arm do not collide with obstacles during the execution of the planned paths and exhibit good stability.关键词
RRT*算法/机械臂路径规划/目标区域引导/三次B样条曲线Key words
RRT* algorithm/manipulator path planning/target area guide/cubic B-spline curve分类
信息技术与安全科学引用本文复制引用
孟月波,张子炜,吴磊,刘光辉,徐胜军..目标区域引导的RRT*机械臂路径规划算法[J].计算机科学与探索,2024,18(9):2407-2421,15.基金项目
陕西省重点研发计划(2021SF-429) （2021SF-429）
陕西省自然科学基础研究计划项目(2023-JC-YB-532). This work was supported by the Key Research and Development Program of Shaanxi Province(2021SF-429),and the Natural Science Basic Research Program of Shaanxi Province(2023-JC-YB-532). （2023-JC-YB-532）
