@inproceedings{5935ca77fd6d44d89f8aad9b7bb3a1cb,
title = "A Practical Multi-camera SLAM System for Large Mobile Robots",
abstract = "It is very important to provide sufficient visual perception for large mobile robots to improve their security and intelligence. Considering the narrow field of vision and insufficient perception of a single camera, this paper proposes a practical multi-camera SLAM system. According to the hardware structure of the large mobile robot, the layout scheme of the multi-camera is designed and its field of view is analyzed. To make full use of the advantages of multi-camera data fusion, a multi-camera localization algorithm based on the main localization module and sub-localization module is proposed. In order to build a dense 3D point cloud map, a novel depth estimation method is present, which first uses the depth estimation method based on camera geometry to obtain a preliminary depth map, and then uses a convolutional neural network to refine it. Comprehensive experiments prove that our multi-camera SLAM system achieves appealing results and has strong practicability.",
keywords = "SLAM, component, dense mapping, depth estimation, multi-camera System",
author = "Yunlong Dong and Hong Ding and Fusheng Zha and Mantian Li",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2nd International Conference on Big Data, Artificial Intelligence and Risk Management, ICBAR 2022 ; Conference date: 25-11-2022 Through 27-11-2022",
year = "2022",
doi = "10.1109/ICBAR58199.2022.00041",
language = "英语",
series = "Proceedings - 2022 2nd International Conference on Big Data, Artificial Intelligence and Risk Management, ICBAR 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "179--184",
booktitle = "Proceedings - 2022 2nd International Conference on Big Data, Artificial Intelligence and Risk Management, ICBAR 2022",
address = "美国",
}