Proximal policy optimization based dynamic path planning algorithm for mobile robots

Xin Jin, Zhengxiao Wang
2021 Electronics Letters  
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.
doi:10.1049/ell2.12342 fatcat:tsfzeordmfecfb2jzhbbdsc364