@inproceedings{99c26fb21f234a9480f76e98ca639df3,
title = "Reinforcement Learning for UAV Autonomous Tracking Random Moving Target",
abstract = "A novel unmanned aerial vehicles (UAVs) autonomous target tracking control method based on Reinforcement Learning (RL) is presented in this article. The policy network controller trained by the RL algorithm replaces the trajectory planning and UAV outer loop controller in the traditional UAV target tracking architecture, and this controller has the advantages of high robustness and less computation. Besides, a model optimization is applied to turn the issue of UAV tracking random moving target to UAV tracking stationary target. In this way, the UAV target tracking question will be more comfortable to apply the RL algorithm to train, and the training result also has strong performance on UAV tracking a random moving target.",
keywords = "Autonomy, Random moving, Reinforcement learning, Target tracking, UAV",
author = "Zhihao Cai and Mingjun Li and Jiang Zhao and Yingxun Wang",
note = "Publisher Copyright: {\textcopyright} 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Guidance, Navigation and Control, ICGNC 2020 ; Conference date: 23-10-2020 Through 25-10-2020",
year = "2022",
doi = "10.1007/978-981-15-8155-7\_93",
language = "英语",
isbn = "9789811581540",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "1109--1121",
editor = "Liang Yan and Haibin Duan and Xiang Yu",
booktitle = "Advances in Guidance, Navigation and Control - Proceedings of 2020 International Conference on Guidance, Navigation and Control, ICGNC 2020",
address = "德国",
}