Improved RRT Path Planning Method Based on Multiple Security Models
ZHU Minhua
REN Mingwu
Abstract：Path planning is the key part of decision-making in the autonomous vehicle system. Due to its low complexity and fast searching speed,the rapidly-expanding random tree(RRT)has been widely used. However,its randomness also results in low efficiency of the algorithm and poor planning path quality. In addition,many path planning algorithms do not consider the risk of dif?ferent obstacles. Therefore,based on the RRT algorithm,this paper introduces the artificial potential field method,proposes an im?proved RRT path planning method based on multiple safety models,and optimizes the planning path to improve the convergence speed of the algorithm and ensure the path security to get an optimal solution. Simulation results show the effectiveness of the algo?rithm.
Keywords：path planningrapidly-expanding random treeartificial potential fieldpath optimization
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1941-1946 )