Bio-inspired Vision Mapping and Localization Method Based on Reprojection Error Optimization and Asynchronous Kalman Fusion
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| Publié dans: | Chinese Journal of Mechanical Engineering = Ji xie gong cheng xue bao vol. 38, no. 1 (Dec 2025), p. 163 |
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| Auteur principal: | |
| Autres auteurs: | , , , , |
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Springer Nature B.V.
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| Accès en ligne: | Citation/Abstract Full Text Full Text - PDF |
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| 024 | 7 | |a 10.1186/s10033-025-01342-3 |2 doi | |
| 035 | |a 3241748185 | ||
| 045 | 2 | |b d20251201 |b d20251231 | |
| 100 | 1 | |a Zhang, Shijie |u Beijing Jiaotong University, School of Automation and Intelligence, Beijing, China (GRID:grid.181531.f) (ISNI:0000 0004 1789 9622) | |
| 245 | 1 | |a Bio-inspired Vision Mapping and Localization Method Based on Reprojection Error Optimization and Asynchronous Kalman Fusion | |
| 260 | |b Springer Nature B.V. |c Dec 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency, rapid dynamic response, and environmental adaptability. Among these, event cameras—bio-inspired sensors that asynchronously report pixel-level brightness changes called 'events', stand out because of their ability to capture dynamic changes with minimal energy consumption, making them suitable for challenging conditions, such as low light or high-speed motion. However, current mapping and localization methods for event cameras depend primarily on point and line features, which struggle in sparse or low-feature environments and are unsuitable for static or slow-motion scenarios. We addressed these challenges by proposing a bio-inspired vision mapping and localization method using active LED markers (ALMs) combined with reprojection error optimization and asynchronous Kalman fusion. Our approach replaces traditional features with ALMs, thereby enabling accurate tracking under dynamic and low-feature conditions. The global mapping accuracy significantly improved by minimizing the reprojection error, with corner errors reduced from 16.8 cm to 3.1 cm after 400 iterations. The asynchronous Kalman fusion of multiple camera pose estimations from ALMs ensures precise localization with a high temporal efficiency. This method achieved a mean translation error of 0.078 m and a rotational error of 5.411° while evaluating dynamic motion. In addition, the method supported an output rate of 4.5 kHz while maintaining high localization accuracy in UAV spiral flight experiments. These results demonstrate the potential of the proposed approach for real-time robot localization in challenging environments. | |
| 653 | |a Robotics | ||
| 653 | |a Localization method | ||
| 653 | |a Simultaneous localization and mapping | ||
| 653 | |a Cameras | ||
| 653 | |a Accuracy | ||
| 653 | |a Vision | ||
| 653 | |a Dynamic response | ||
| 653 | |a Optimization | ||
| 653 | |a Sensors | ||
| 653 | |a Mapping | ||
| 653 | |a Methods | ||
| 653 | |a Errors | ||
| 653 | |a Pose estimation | ||
| 653 | |a Localization | ||
| 653 | |a Real time | ||
| 653 | |a Energy consumption | ||
| 653 | |a Efficiency | ||
| 700 | 1 | |a Tang, Tao |u Beijing Jiaotong University, School of Automation and Intelligence, Beijing, China (GRID:grid.181531.f) (ISNI:0000 0004 1789 9622) | |
| 700 | 1 | |a Hou, Taogang |u Beijing Jiaotong University, School of Automation and Intelligence, Beijing, China (GRID:grid.181531.f) (ISNI:0000 0004 1789 9622) | |
| 700 | 1 | |a Huang, Yuxuan |u Beijing Jiaotong University, School of Automation and Intelligence, Beijing, China (GRID:grid.181531.f) (ISNI:0000 0004 1789 9622) | |
| 700 | 1 | |a Pei, Xuan |u Beijing Jiaotong University, School of Automation and Intelligence, Beijing, China (GRID:grid.181531.f) (ISNI:0000 0004 1789 9622) | |
| 700 | 1 | |a Wang, Tianmiao |u Beihang University, School of Mechanical Engineering and Automation, Beijing, China (GRID:grid.64939.31) (ISNI:0000 0000 9999 1211) | |
| 773 | 0 | |t Chinese Journal of Mechanical Engineering = Ji xie gong cheng xue bao |g vol. 38, no. 1 (Dec 2025), p. 163 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3241748185/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3241748185/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3241748185/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |