@inproceedings{144a5d6cd1c24ef3b2986b2b6a93526b,
title = "UAV Target Tracking Method Based on Deep Reinforcement Learning",
abstract = "This study proposes a UAV target tracking method using reinforcement learning algorithm combined with Gate Recurrent Unit (GRU) to promote UAV target tracking and visual navigation in complex environment. Firstly, an algorithm Twins Delayed Deep Deterministic policy gradient algorithm (TD3) using deep reinforcement learning and the GRU gated loop unit are introduced. The unit is then added to the neural network to process continuous time data, and the algorithm TD3 is adopted to train the model so that it can drive the UAV to make autonomous flight decisions and accomplish target tracking. The proposed method is verified on the AirSim simulation platform.",
keywords = "GRU, TD3, UAV target tracking, visual navigation",
author = "Haohui Zhang and Pingkuan He and Ming Zhang and Daqing Chen and Evgeny Neretin and Bo Li",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 International Conference on Cyber-Physical Social Intelligence, ICCSI 2022 ; Conference date: 18-11-2022 Through 21-11-2022",
year = "2022",
doi = "10.1109/ICCSI55536.2022.9970588",
language = "英语",
series = "Proceedings of the International Conference on Cyber-Physical Social Intelligence, ICCSI 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "274--277",
editor = "Xuemin Chen and Jun Wang and Jiacun Wang and Ying Tang",
booktitle = "Proceedings of the International Conference on Cyber-Physical Social Intelligence, ICCSI 2022",
}