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- W3080976073 abstract "<h3>Abstract</h3> We propose a Simultaneous Localization and Mapping (SLAM)-based Integrity Monitoring (IM) algorithm using GPS and fish-eye camera to compute the protection levels while accounting for multiple faults in GPS and vision. We perform graph optimization using GPS pseudoranges, pixel intensities, vehicle dynamics, and satellite ephemeris to simultaneously localize the vehicle, GPS satellites, and key image pixels in the world frame. We estimate the fault mode vector by analyzing the temporal correlation across pseudorange residuals and spatial correlation across pixel intensity residuals. To isolate the vision faults, we develop a superpixel-based piecewise random sample consensus. For the estimated fault mode, we compute the protection levels by performing worst-case failure slope analysis on the batch realization of linearized Graph-SLAM formulation. We perform real-world experiments in an alleyway in Stanford, California and a semi-urban area in Champaign, Illinois. We demonstrate higher localization accuracy and tighter protection levels as compared to GPS-only SLAM-based IM." @default.
- W3080976073 created "2020-09-01" @default.
- W3080976073 creator A5069625302 @default.
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- W3080976073 date "2020-08-24" @default.
- W3080976073 modified "2023-10-03" @default.
- W3080976073 title "Integrity monitoring of Graph‐SLAM using GPS and fish‐eye camera" @default.
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- W3080976073 doi "https://doi.org/10.1002/navi.381" @default.
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