Simultaneous Localization and Mapping (SLAM) is a technique that estimates a self-position while simultaneously constructing a map of the surrounding environment. In SLAM, errors in the estimated self-position can significantly affect overall performance. Global Bundle Adjustment (GBA) is a widely used optimization process intended to correct such errors and improve estimation accuracy. While GBA often enhances trajectory accuracy, in some cases it can introduce substantial degradation. To address this problem, we propose Motion Check (MC), a method that compares the estimated trajectories pre- and post-GBA. When a significant discrepancy in trajectory shape is observed, the method judges that GBA has caused a deterioration in accuracy. By identifying points where accuracy degrades due to GBA and applying appropriate corrective actions, Motion Check effectively suppresses such deterioration. In evaluations using the EuRoC dataset, Motion Check demonstrated its effectiveness by reducing the maximum trajectory error by up to 81.52cm and the root mean square error by up to 3.40cm.
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Mizushima et al. (Thu,) studied this question.
synapsesocial.com/papers/69a76127c6e9836116a2ed1a — DOI: https://doi.org/10.2197/ipsjjip.34.103
Taishi Mizushima
Naoki Matsushita
Hiroshi Shigeno
Journal of Information Processing
Keio University
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