Path Planning of Manipulators Based on the Norm Adaptive Step-size RRT Algorithm
Liu Yafei
Liu Fang
Dong Rong
Wu Baoning
Nie Shaoqing
Abstract：A norm adaptive step size rapidly-exploring random tree(RRT)algorithm suitable for manipu-lators was proposed to address the issues of fixed step size debugging time,poor collision detection performance,and low search efficiency of the traditional RRT algorithm in multidimensional environments.Firstly,a kinemat-ic model with a 6-degree-of-freedom UR5 manipulator was established,and the forward kinematic analysis was performed.Secondly,by combining the norm inequality and the Jacobian matrix,a step mapping relation be-tween the workspace of the manipulator and the joint space was constructed,dynamically changing the search step size of the joint space while ensuring the effectiveness of collision detection.Finally,the simulation analysis results show that the norm adaptive step size RRT algorithm has higher search efficiency than the traditional fixed step size RRT algorithm and does not require the manual step size adjustment,and the path search time has been reduced by 29.32％,thus improving the efficiency of manipulator path planning.
Keywords：Path planningManipulatorRRTAdaptive step-sizeKinematic
Publication Date：2024-12-15
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：5( 82-86 )