A LiDAR/Visual SLAM Backend with Loop Closure Detection and Graph Optimization
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| Publicado en: | Remote Sensing vol. 13, no. 14 (2021), p. 2720 |
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| Autor principal: | |
| Otros Autores: | , , , |
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MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2072-4292 | ||
| 024 | 7 | |a 10.3390/rs13142720 |2 doi | |
| 035 | |a 2554746408 | ||
| 045 | 2 | |b d20210101 |b d20211231 | |
| 084 | |a 231556 |2 nlm | ||
| 100 | 1 | |a Chen, Shoubin |u Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China; <email>shoubin.chen@whu.edu.cn</email> (S.C.); <email>weixingxue@whu.edu.cn</email> (W.X.); <email>liqq@szu.edu.cn</email> (Q.L.); School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China; Orbbec Research, Shenzhen 518052, China | |
| 245 | 1 | |a A LiDAR/Visual SLAM Backend with Loop Closure Detection and Graph Optimization | |
| 260 | |b MDPI AG |c 2021 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a LiDAR (light detection and ranging), as an active sensor, is investigated in the simultaneous localization and mapping (SLAM) system. Typically, a LiDAR SLAM system consists of front-end odometry and back-end optimization modules. Loop closure detection and pose graph optimization are the key factors determining the performance of the LiDAR SLAM system. However, the LiDAR works at a single wavelength (905 nm), and few textures or visual features are extracted, which restricts the performance of point clouds matching based loop closure detection and graph optimization. With the aim of improving LiDAR SLAM performance, in this paper, we proposed a LiDAR and visual SLAM backend, which utilizes LiDAR geometry features and visual features to accomplish loop closure detection. Firstly, the bag of word (BoW) model, describing the visual similarities, was constructed to assist in the loop closure detection and, secondly, point clouds re-matching was conducted to verify the loop closure detection and accomplish graph optimization. Experiments with different datasets were carried out for assessing the proposed method, and the results demonstrated that the inclusion of the visual features effectively helped with the loop closure detection and improved LiDAR SLAM performance. In addition, the source code, which is open source, is available for download once you contact the corresponding author. | |
| 653 | |a Feature extraction | ||
| 653 | |a Cameras | ||
| 653 | |a Accuracy | ||
| 653 | |a Source code | ||
| 653 | |a Matching | ||
| 653 | |a Lidar | ||
| 653 | |a Optimization | ||
| 653 | |a Sensors | ||
| 653 | |a Mapping | ||
| 653 | |a Methods | ||
| 653 | |a Algorithms | ||
| 653 | |a Localization | ||
| 653 | |a Radiation | ||
| 653 | |a Simultaneous localization and mapping | ||
| 700 | 1 | |a Zhou, Baoding |u Institute of Urban Smart Transportation & Safety Maintenance, Shenzhen University, Shenzhen 518060, China; <email>bdzhou@szu.edu.cn</email>; Key Laboratory for Resilient Infrastructures of Coastal Cities (Shenzhen University), Ministry of Education, Shenzhen 518060, China | |
| 700 | 1 | |a Jiang, Changhui |u Department of Photogrammetry and Remote Sensing, Finnish Geospatial Research Institute (FGI), FI-02430 Masala, Finland | |
| 700 | 1 | |a Xue, Weixing |u Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China; <email>shoubin.chen@whu.edu.cn</email> (S.C.); <email>weixingxue@whu.edu.cn</email> (W.X.); <email>liqq@szu.edu.cn</email> (Q.L.) | |
| 700 | 1 | |a Li, Qingquan |u Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China; <email>shoubin.chen@whu.edu.cn</email> (S.C.); <email>weixingxue@whu.edu.cn</email> (W.X.); <email>liqq@szu.edu.cn</email> (Q.L.); School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China | |
| 773 | 0 | |t Remote Sensing |g vol. 13, no. 14 (2021), p. 2720 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2554746408/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/2554746408/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2554746408/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |