@inproceedings{748567b559e34c0ba1425ffa6de33fd9,
title = "Optimal Formation-Containment Control for A Cooperative Unmanned Air-Ground Vehicle Group Under Switching Topologies",
abstract = "The problem of optimal formation-containment control for groups of heterogenous unmanned air-ground vehicles (UA-GVs) under switching topologies is solved using reinforcement learning (RL) techniques. The quadrotor dynamics exhibit underactuation, and the dynamics of the UA-GV system are nonlinear and involving uncertain parameters. Positional estimators are devised for each agent to deliver references subject to the impact resulted from topological changes. Optimal control strategies are formulated without precise knowledge of the inertial parameters of the agents. Simulation examples are demonstrated, confirming the efficacy of the devised optimal control strategies.",
keywords = "containment control, formation control, heterogenous system, optimal control",
author = "Hao Liu and Ming Cheng and Qing Gao and Haibin Duan",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.; International Conference on Guidance, Navigation and Control, ICGNC 2024 ; Conference date: 09-08-2024 Through 11-08-2024",
year = "2025",
doi = "10.1007/978-981-96-2248-1\_10",
language = "英语",
isbn = "9789819622474",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "96--106",
editor = "Liang Yan and Haibin Duan and Yimin Deng",
booktitle = "Advances in Guidance, Navigation and Control - Proceedings of 2024 International Conference on Guidance, Navigation and Control Volume 13",
address = "德国",
}