Redesigning SLAM for Arbitrary Multi-Camera Systems
- URL: http://arxiv.org/abs/2003.02014v1
- Date: Wed, 4 Mar 2020 11:44:42 GMT
- Title: Redesigning SLAM for Arbitrary Multi-Camera Systems
- Authors: Juichung Kuo, Manasi Muglikar, Zichao Zhang, Davide Scaramuzza
- Abstract summary: Adding more cameras to SLAM systems improves robustness and accuracy but complicates the design of the visual front-end significantly.
In this work, we aim at an adaptive SLAM system that works for arbitrary multi-camera setups.
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.
- Score: 51.81798192085111
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
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