@inproceedings{7857f34b4fd74db5a048a6b39c410914,
title = "Towards Pose Estimation for Large UAV in Close Range",
abstract = "This paper deals with the problem of 4D pose estimation for large unmanned aerial vehicles (UAVs) in close range. A sensor system consisting of one single point laser range-finder and two cameras is designed and a novel pose estimation method based on vision fusion and point cloud registration is proposed. Our approach works on one-shot mode and only requires 10 samples with real poses for template construction. Through V-rep simulation environment, we generate two 200-sample datasets of different difficulty for evaluation. Error quantiles, 5cm5deg and 10cml0deg are three evaluation metrics used in our ablation experiments. It is illustrated that our method outperforms in robustness and precision due to proposed dimension extension modification and fusion of vision sensors.",
keywords = "UAV, point cloud registration, pose estimation, sensor fusion",
author = "Ni Ou and Junzheng Wang and Shangfei Liu and Jiehao Li",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022 ; Conference date: 19-11-2022 Through 20-11-2022",
year = "2022",
doi = "10.1109/YAC57282.2022.10023647",
language = "English",
series = "Proceedings - 2022 37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "56--61",
booktitle = "Proceedings - 2022 37th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2022",
address = "United States",
}