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| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Redesigning SLAM for Arbitrary Multi-Camera Systems |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| ISBN | 978-1-7281-7395-5 |
| Page Range | 2116 - 2122 |
| Event Title | 2020 IEEE International Conference on Robotics and Automation (ICRA) |
| Event Type | conference |
| Event Location | Paris, France |
| Event Start Date | July 1 - 2020 |
| Event End Date | October 1 - 2020 |
| Publisher | IEEE |
| Abstract Text | Adding more cameras to SLAM systems improves robustness and accuracy but complicates the design of the visual front-end significantly. Thus, most systems in the literature are tailored for specific camera configurations. In this work, we aim at an adaptive SLAM system that works for arbitrary multi-camera setups. To this end, we revisit several common building blocks in visual SLAM. In particular, we propose an adaptive initialization scheme, a sensor-agnostic, information- theoretic keyframe selection algorithm, and a scalable voxel- based map. These techniques make little assumption about the actual camera setups and prefer theoretically grounded methods over heuristics. We adapt a state-of-the-art visual- inertial odometry with these modifications, and experimental results show that the modified pipeline can adapt to a wide range of camera setups (e.g., 2 to 6 cameras in one experiment) without the need of sensor-specific modifications or tuning. |
| Digital Object Identifier | 10.1109/icra40945.2020.9197553 |
| Other Identification Number | merlin-id:20307 |
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