@inproceedings{ec650f04c1714ce385e748707ea20f90,
title = "A Registration Framework for Air-ground Point Cloud Maps",
abstract = "Due to different perspectives, there are significant discrepancies between air-ground point cloud maps in density and blind area, which is a huge challenge for map registration of air-ground collaborative unmanned system. To solve these problems, we design a point cloud map registration framework based on feature error between maps. Firstly, we extract and fuse the features of point cloud maps from aerial and ground. Then the feature error between fusion features and air features is calculated and the optimal registration from ground-map to air-map is estimated by minimizing feature error. Finally, experimental report the accuracy under the initial rotation error of 80 degrees and random translation.",
keywords = "air-ground cooperation, feature error, map registration",
author = "Man Zhang and Yi Yang and Junbo Wang and Linzhe Shi and Yufeng Yue and Mengyin Fu",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Unmanned Systems, ICUS 2021 ; Conference date: 15-10-2021 Through 17-10-2021",
year = "2021",
doi = "10.1109/ICUS52573.2021.9641378",
language = "English",
series = "Proceedings of 2021 IEEE International Conference on Unmanned Systems, ICUS 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "63--68",
booktitle = "Proceedings of 2021 IEEE International Conference on Unmanned Systems, ICUS 2021",
address = "United States",
}