Simultaneous path following and obstacle avoidance of field-tracked vehicles via model predictive control with deep deterministic policy gradient

Yu-Cheng Sung; Chun-Ting Sung; Wen-Chuan Tseng; Shean-Jen Chen

doi:10.1117/12.2621549

20 May 2022 Simultaneous path following and obstacle avoidance of field-tracked vehicles via model predictive control with deep deterministic policy gradient

Yu-Cheng Sung, Chun-Ting Sung, Wen-Chuan Tseng, Shean-Jen Chen

Author Affiliations +

Proceedings Volume 12137, Optics and Photonics for Advanced Dimensional Metrology II; 121370N (2022) https://doi.org/10.1117/12.2621549
Event: SPIE Photonics Europe, 2022, Strasbourg, France

Abstract

Unmanned ground vehicles (UGVs) will be widely adopted in agricultural applications. To accomplish autonomous cruising in farm, path following is an essential skill. However, in the process of field cruising, some obstacles such as wild animals or motorcycles are present. In this study, tracked vehicles are utilized with deep deterministic policy gradient (DDPG) compensating for model uncertainties and achieving collision avoidance simultaneously. Among all, the most important issue is to keep the UGV following the predetermined path in specific agricultural field environment and coping with the uncertainty of the surroundings. Path following and obstacle avoidance of field tracked vehicles are conducted by using model predictive control (MPC) with a controller (agent) trained by DDPG. Therefore, we proposed control algorithm fusion with MPC and model-free DDPG.

Conference Presentation

Citation Download Citation

Yu-Cheng Sung, Chun-Ting Sung, Wen-Chuan Tseng, and Shean-Jen Chen "Simultaneous path following and obstacle avoidance of field-tracked vehicles via model predictive control with deep deterministic policy gradient", Proc. SPIE 12137, Optics and Photonics for Advanced Dimensional Metrology II, 121370N (20 May 2022); https://doi.org/10.1117/12.2621549

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