1. Robust Positioning from Visual-Inertial and GPS Measurements
- Author
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Venkatesan Nallampatti Ekambaram, Lionel Jacques Garin, Urs Niesen, Jubin Jose, and Xinzhou Wu
- Subjects
Precision Lightweight GPS Receiver ,Percentile ,Inertial frame of reference ,Odometry ,Computer science ,business.industry ,Outlier ,Global Positioning System ,Gps positioning ,Computer vision ,Artificial intelligence ,business ,Physics::Geophysics - Abstract
GPS positioning in urban scenarios is challenging because of large numbers of non-line-of-sight outlier measurements. In this paper we propose a robust positioning algorithm that combines GPS observations with visual-inertial odometry information to handle such outliers. We demonstrate the effectiveness of our algorithm in a simulation scenario with close to 80% outliers. In experiments in a mild urban-canyon environment, our approach reduces the 95th percentile horizontal positioning error by 66% compared to a GPS-only solution.
- Published
- 2016
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