Robotic Arm Motion Planning Based on an Improved PRM
You Dazhang
Zhao Hengyi
Song Luwen
Abstract：In order to solve the problems such as low efficiency,route redundancy and insufficient smooth-ness of the traditional probabilistic roadmap method(PRM),an improved PRM was proposed for obstacle avoid-ance path planning of manipulators.Sobol sequence sampling method was used to improve the connectivity of probabilistic road map and the success rate of the algorithm.Redundant node pruning and progressive route pruning based on dichotomous interpolation were adopted to make the path more approximate to the optimal so-lution.Finally,the path was smoothed by using the quintic polynomial interpolation method to make the motion of the manipulator more stable and smoother.The simulation results show that the improved PRM can improve the success rate of path planning,optimize the path,reduce the number of nodes and path length,and the manip-ulator is more uniform and smoother.The experiment proves that the method can effectively and reasonably real-ize the obstacle avoidance and path planning of the manipulator.
Keywords：Motion planningProbabilistic roadmap methodSobol sequence samplingPath optimiza-tionQuintic polynomial interpolation
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：8( 87-93,148 )