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Path Planning Method of Robot Arm Based on Improved RRT* Algorithm

Ji‐Xiang Du, Changqing Cai, Peisen Zhang, Jianwen Tan

202213 citationsDOI

Abstract

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 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">*</sup> (rapid random search tree) algorithm was proposed. First, in order to reduce the randomness of the traditional RRT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">*</sup> 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 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">*</sup> 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 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">*</sup> 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.

Topics & Concepts

AlgorithmMotion planningPath (computing)Computer scienceConvergence (economics)Artificial intelligenceMathematicsRobotProgramming languageEconomicsEconomic growthRobotic Path Planning AlgorithmsRobotics and Sensor-Based LocalizationControl and Dynamics of Mobile Robots
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