@inproceedings{2762530d0b1d42488cafc2f6a006d21f,
title = "Scene-Matching Localization for Autonomous Evtol Based on Bag-Of-Visual-Words",
abstract = "With the rapid growth of urban air mobility (UAM) and the potential market opportunities it presents, achieving precise and reliable localization for electrical vertical takeoff and landing (eVTOL) aircraft is crucial. Traditional global navigation satellite system (GNSS) based methods suffer from reliability issues, making localization without GNSS a pressing need. This paper presents a scene-matching localization method based on Bag-of-Visual-Words (BOVW) for autonomous eVTOL. The proposed method overcomes challenges of environmental differences between live images and reference maps, as well as the computational limitations of existing solutions. The system utilizes on-cloud training, on-cloud encoding, and onboard localization stages to ensure robust localization performance. Real-world experiments on an eVTOL prototype- ZJ-Copter validate the effectiveness of the approach, with a matching success rate exceeding 94\% and localization accuracy within 3 meters. The method holds promise as a GNSS-independent localization solution for autonomous eVTOLs in the emerging field of UAM.",
keywords = "BOVW, GNSS-denied environment, autonomous eVTOL, localization, scene-matching",
author = "Senwei Xiang and Minxiang Ye and Ting Wang and Yifei Zhang and Zehua Men and Anhuan Xie",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 ; Conference date: 16-07-2023 Through 21-07-2023",
year = "2023",
doi = "10.1109/IGARSS52108.2023.10282008",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4772--4775",
booktitle = "IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings",
address = "美国",
}