@inproceedings{b63423a5fda84c069ee73e11a542d11a,
title = "FFCN: Flexible Fusion for AUV Swarm Cooperative Navigation",
abstract = "Autonomous underwater vehicle (AUV), as an indispensable tool for exploring the ocean, has developed rapidly in recent years. With the gradual deepening of people's exploration of the ocean, a single underwater vehicle detection range and detection capacity are limited to meet large-scale and long-term operational requirements. Therefore, the coordinated operation of the multi-AUV has become an important direction for the development of underwater vehicles. The precise navigation result is the premise of the AUV cluster execution task. A multi-AUV collaborative navigation method based on flexible fusion ideas is proposed for sensor failures caused by complex underwater environments and the interruption of water acoustic communication. Flexible fusion refers to the elastic selection of suitable sensor groups according to different operational conditions and different operational tasks under the premise of ensuring cluster navigation accuracy, and the weighted fusion of data based on the principle of minimizing navigation errors to avoid navigation accuracy degradation due to insufficient sensor accuracy or failure.",
keywords = "Cooperative navigation, Extended kalman filter, Flexible fusion, Neural network",
author = "Yue Chen and Tong Zhang and Jun Liu and Wenxue Guan",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Conference on Intelligent Communication and Networking, ICN 2023 ; Conference date: 10-11-2023 Through 12-11-2023",
year = "2023",
doi = "10.1109/ICN60549.2023.10426558",
language = "英语",
series = "2023 International Conference on Intelligent Communication and Networking, ICN 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "196--201",
booktitle = "2023 International Conference on Intelligent Communication and Networking, ICN 2023",
address = "美国",
}