基于改进RRT*算法的机械臂路径规划方法

Jixiang Du, Changqing Cai, Peisen Zhang, Jianwen Tan
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引用次数: 2

摘要

针对机械臂路径规划中规划时间长、路径距离长等问题,提出了一种基于改进RRT*(快速随机搜索树)算法的路径规划策略。首先,为了降低传统RRT*路径搜索的随机性,加入节点重力场函数可以减少冗余节点的产生,从而提高路径收敛速度;其次,为了改变传统RRT*算法路径中存在的折叠问题,引入b样条函数对规划路径进行平滑处理,降低了关节轴的振动,延长了机械臂的使用寿命;MATLAB仿真结果表明,改进后的RRT*算法平均规划时间缩短76%,平均路径距离缩短14%,节点总数减少31.9%。改进算法后,直线收敛速度快,寻线效率高。该算法具有良好的可行性和有效性,对机械臂路径规划具有参考价值。
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Path Planning Method of Robot Arm Based on Improved RRT* Algorithm
Aiming at the problems of long planning time and long path distance in the path planning of the robotic arm, a path planning strategy based on the improved RRT* (rapid random search tree) algorithm was proposed. First, in order to reduce the randomness of the traditional RRT* path search, adding the node gravitational field function could reduce the generation of redundant nodes, thereby improving the path convergence rate; Secondly, in order to change the folding problem in the traditional RRT* algorithm path, the B-spline function was imported to smooth the planned path, which could reduce the vibration of the joint axis and prolong the service life of the robotic arm. Simulations in MATLAB showed that the average planning time of the improved RRT* algorithm was shortened by 76%, the average path distance was shortened by 14%, and the total number of nodes was reduced by 31.9%. After improving the algorithm, the lines convergence quickly and the line -seeking efficiency is high. The algorithm has good feasibility and effectiveness, and has reference value for the planning of robotic arm path.
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