Open AccessProximal policy optimization based dynamic path planning algorithm for mobile robots
Author(s) -
Jin Xin,
Wang Zhengxiao
Publication year - 2022
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/ell2.12342
Subject(s) - motion planning , computer science , obstacle , path (computing) , algorithm , obstacle avoidance , mobile robot , optimization algorithm , state (computer science) , robot , mathematical optimization , artificial intelligence , mathematics , political science , law , programming language
Abstract For the scenario where the overall layout is known and the obstacle distribution information is unknown, a dynamic path planning algorithm combining the A* algorithm and the proximal policy optimization (PPO) algorithm is proposed. Simulation experiments show that in all six test environments, the proposed algorithm finds paths that are on average about 2.04% to 5.86% shorter compared to the state‐of‐the‐art algorithms in the literature, and reduces the number of training epochs before stabilization from tens of thousands to about 4000.