Research on path planning algorithm of unmanned ground platform based on reinforcement learning

Pei Zhang; Cheng Ye Zhang; Wei Long Gai

doi:10.1117/12.2671690

28 April 2023 Research on path planning algorithm of unmanned ground platform based on reinforcement learning

Pei Zhang, Cheng Ye Zhang, Wei Long Gai

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 1261054 (2023) https://doi.org/10.1117/12.2671690
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Path planning algorithm is the basis of unmanned ground platform to realize unmanned driving function. Traditional path planning algorithms mostly regard path planning as a geometric problem, which has great limitations on the work of unmanned platforms in the current complex environment. The reinforcement learning algorithm focuses on online planning and has the advantage of continuing to explore and find better solutions on the basis of effective actions. This paper studies path planning of unmanned ground platform based on reinforcement learning method. Aiming at the problems of low flexibility and slow convergence of the current reinforcement learning method in path planning, this paper improves the Q-learning algorithm based on the reinforcement learning algorithm and conducts simulation experiments and analyzes the experimental results. The analysis shows that the path planning algorithm of unmanned ground platform based on reinforcement learning has obvious advantages in performance.

Citation Download Citation

Pei Zhang, Cheng Ye Zhang, and Wei Long Gai "Research on path planning algorithm of unmanned ground platform based on reinforcement learning", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 1261054 (28 April 2023); https://doi.org/10.1117/12.2671690

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