@inproceedings{05814d12f9ee4ab589e828351faa1780,
title = "Robust Optimal Formation Control of Heterogeneous Air-Ground Vehicles Under Communication Faults via Reinforcement Learning",
abstract = "This paper develops a robust optimal formation protocol for multiple vehicles subject to communication faults via the reinforcement learning method. The nonlinearities and external disturbances in the vehicle dynamics and the communication faults among heterogeneous team are considered and a data-based robust coordination protocol is developed using only the local interaction information between vehicles. Simulation results of heterogeneous air-ground vehicles achieving the position coordination and yaw angle synchronization are presented to validate the proposed approach.",
keywords = "Air-ground coordination, Communication faults, Heterogeneous vehicles, Reinforcement learning, Robust optimal formation control",
author = "Wanbing Zhao and Hao Liu and Qing Gao and Jinhu L{\"u}",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; International Conference on Guidance, Navigation and Control, ICGNC 2022 ; Conference date: 05-08-2022 Through 07-08-2022",
year = "2023",
doi = "10.1007/978-981-19-6613-2\_404",
language = "英语",
isbn = "9789811966125",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "4145--4155",
editor = "Liang Yan and Haibin Duan and Yimin Deng and Liang Yan",
booktitle = "Advances in Guidance, Navigation and Control - Proceedings of 2022 International Conference on Guidance, Navigation and Control",
address = "德国",
}