Robust loop closure detection and relocalization with semantic-line graph matching constraints in indoor environments
Loop closure detection (LCD) plays an essential role in the Simultaneous Localization and Mapping (SLAM) process, effectively reducing cumulative trajectory errors. However, conventional LCD methods often encounter challenges when dealing with variations in illumination, changes in viewpoint, and en...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-05-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843224001985 |
| _version_ | 1797200877681901568 |
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| author | Xiqi Wang Shunyi Zheng Xiaohu Lin Qiyuan Zhang Xiaojian Liu |
| author_facet | Xiqi Wang Shunyi Zheng Xiaohu Lin Qiyuan Zhang Xiaojian Liu |
| author_sort | Xiqi Wang |
| collection | DOAJ |
| description | Loop closure detection (LCD) plays an essential role in the Simultaneous Localization and Mapping (SLAM) process, effectively reducing cumulative trajectory errors. However, conventional LCD methods often encounter challenges when dealing with variations in illumination, changes in viewpoint, and environments with weak textures. This is due to their reliance on low-level geometric or image features. To address these issues, we propose a robust LCD method named SL-LCD, which integrates semantic information and line features to fully leverage the semantic content and line attributes within indoor scenes, thereby establishing a reliable feature correspondence between query images and loop closure images. For the retrieval of candidate closed-loop images, we construct a semantic-line-segment topological graph and introduce a graph matching algorithm to perform the LCD task. This approach fully exploits image features and spatial information to achieve closed-loop detection in complex indoor scenes. Furthermore, we present a semantic voxel-based generalized ICP (SVGICP) closed-loop relocalization algorithm tailored for challenging and complex indoor scenes, enhancing the accuracy of closed-loop relocalization in such scenarios. Experimental results demonstrate that the SL-LCD algorithm proposed in this paper surpasses state-of-the-art methods, accurately detecting closed loops, and effectively eliminating trajectory drift. |
| first_indexed | 2024-04-24T07:38:38Z |
| format | Article |
| id | doaj.art-643a0e322af84e1397bb1e10721c1123 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-24T07:38:38Z |
| publishDate | 2024-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-643a0e322af84e1397bb1e10721c11232024-04-20T04:17:16ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322024-05-01129103844Robust loop closure detection and relocalization with semantic-line graph matching constraints in indoor environmentsXiqi Wang0Shunyi Zheng1Xiaohu Lin2Qiyuan Zhang3Xiaojian Liu4School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, Hubei, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, Hubei, China; Corresponding author.College of Geomatics, Xi’an University of Science and Technology, Xi’an, 710054, Shanxi, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, Hubei, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, Hubei, ChinaLoop closure detection (LCD) plays an essential role in the Simultaneous Localization and Mapping (SLAM) process, effectively reducing cumulative trajectory errors. However, conventional LCD methods often encounter challenges when dealing with variations in illumination, changes in viewpoint, and environments with weak textures. This is due to their reliance on low-level geometric or image features. To address these issues, we propose a robust LCD method named SL-LCD, which integrates semantic information and line features to fully leverage the semantic content and line attributes within indoor scenes, thereby establishing a reliable feature correspondence between query images and loop closure images. For the retrieval of candidate closed-loop images, we construct a semantic-line-segment topological graph and introduce a graph matching algorithm to perform the LCD task. This approach fully exploits image features and spatial information to achieve closed-loop detection in complex indoor scenes. Furthermore, we present a semantic voxel-based generalized ICP (SVGICP) closed-loop relocalization algorithm tailored for challenging and complex indoor scenes, enhancing the accuracy of closed-loop relocalization in such scenarios. Experimental results demonstrate that the SL-LCD algorithm proposed in this paper surpasses state-of-the-art methods, accurately detecting closed loops, and effectively eliminating trajectory drift.http://www.sciencedirect.com/science/article/pii/S1569843224001985Loop closure detectionSemantic segmentationSLAMGraph matchingRelocalization |
| spellingShingle | Xiqi Wang Shunyi Zheng Xiaohu Lin Qiyuan Zhang Xiaojian Liu Robust loop closure detection and relocalization with semantic-line graph matching constraints in indoor environments International Journal of Applied Earth Observations and Geoinformation Loop closure detection Semantic segmentation SLAM Graph matching Relocalization |
| title | Robust loop closure detection and relocalization with semantic-line graph matching constraints in indoor environments |
| title_full | Robust loop closure detection and relocalization with semantic-line graph matching constraints in indoor environments |
| title_fullStr | Robust loop closure detection and relocalization with semantic-line graph matching constraints in indoor environments |
| title_full_unstemmed | Robust loop closure detection and relocalization with semantic-line graph matching constraints in indoor environments |
| title_short | Robust loop closure detection and relocalization with semantic-line graph matching constraints in indoor environments |
| title_sort | robust loop closure detection and relocalization with semantic line graph matching constraints in indoor environments |
| topic | Loop closure detection Semantic segmentation SLAM Graph matching Relocalization |
| url | http://www.sciencedirect.com/science/article/pii/S1569843224001985 |
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