@inproceedings{21bfbecdcf964ccd8687cb65bd48133b,
title = "Loop Closure Detection Based on Geometry of Semantic Point Cloud",
abstract = "The spatiotemporal constraints provided by loop closure detection play a crucial role in the simultaneous localization and mapping of robots. Traditional methods based on key points information are vulnerable to point-level feature instability. In this paper, a loop closure detection method based on robust geometry of the objects extracted through semantics of point cloud is proposed. Our method is based on the fact that point cloud can robustly describe geometric properties, and the extracted local features are extremely robust and invariant to rotation, thus achieving remarkable results in loop closure detection. We conduct experiments on the KITTI odometry dataset and confirm the effectiveness of our method.",
author = "Danyang Cao and Zhanggang Lyu and Zhong Liu and Haosong Yue and Xingming Wu and Weihai Chen",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023 ; Conference date: 18-08-2023 Through 22-08-2023",
year = "2023",
doi = "10.1109/ICIEA58696.2023.10241501",
language = "英语",
series = "Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1668--1673",
editor = "Wenjian Cai and Guilin Yang and Jun Qiu and Tingting Gao and Lijun Jiang and Tianjiang Zheng and Xinli Wang",
booktitle = "Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023",
address = "美国",
}