Global path planning of mobile robot based on adaptive sampling area RRT Online publication date: Mon, 08-Jul-2024
by Zhixiang Hou; Xiao Tian; Fengling Li; Liefeng Hu
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 16, No. 3, 2024
Abstract: This paper proposed an adaptive sampling area RRT (ASA-RRT) algorithm. Firstly, this paper designs an adaptive sampling region method, which determines the next sampling interval according to the new nodes generated each time, and gradually shrinks the sampling region to reduce sampling in unnecessary regions. Secondly, the target point guidance and greedy strategy are used to strengthen the directionality and convergence speed of the algorithm expansion. Finally, the reverse optimisation algorithm is used for post-processing to eliminate the redundant nodes in the path and shorten the path length. In the simulation environment, the ASA-RRT algorithm is applied to the path planning of the mobile robot. The simulation results show that compared with the basic RRT and target deflection RRT algorithms, the search time, number of sampling points and long path length of the ASA-RRT algorithm are lower by74.05%, 89.08% and 22.45%; 32.67%, 65.07% and 15.61%.
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