@inproceedings{1514eb77090d46d584ac2c8fbac315d9,
title = "Distributed Formation Control and Collision Avoidance for Heterogeneous UAV Swarm",
abstract = "This paper proposes a formation and collision avoidance method for heterogeneous swarm consisting of Unmanned Aerial Vehicles (UAVs) with variable detection abilities. First of all, preliminary knowledge such as the kinematic model of UAV and Particle Swarm Optimization (PSO) algorithm is introduced. Then, the proposed method based on Distributed Model Predictive Control (DMPC) is expressed in detail by dividing UAVs into heterogeneous roles and designing cost functions for different roles according to task requirements. A coordination strategy is further proposed to dissolve the conflict between formation maintenance and collision avoidance. Numerical simulations further demonstrate that the method effectively applies to the formation and collision avoidance task of heterogeneous UAV swarm. Finally, further research direction and potential improvements are discussed.",
keywords = "Distributed model predictive control, Formation and collision avoidance, Heterogeneous UAV, Heterogeneous roles",
author = "Pei Chi and Xuan Zhang and Kun Wu and Lili Zheng and Jiang Zhao and Yingxun Wang",
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\_180",
language = "英语",
isbn = "9789811966125",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "1837--1848",
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",
}