Robust, High-Precision GNSS Carrier-Phase Positioning with Visual-Inertial Fusion
Dong, Erqun, Sheriffdeen, Sheroze, Yang, Shichao, Dong, Jing, De Nardi, Renzo, Ren, Carl, Chang, Xiao-Wen, Liu, Xue, Wang, Zijian
–arXiv.org Artificial Intelligence
Robust, high-precision global localization is fundamental to a wide range of outdoor robotics applications. Conventional fusion methods use low-accuracy pseudorange based GNSS measurements ($>>5m$ errors) and can only yield a coarse registration to the global earth-centered-earth-fixed (ECEF) frame. In this paper, we leverage high-precision GNSS carrier-phase positioning and aid it with local visual-inertial odometry (VIO) tracking using an extended Kalman filter (EKF) framework that better resolves the integer ambiguity concerned with GNSS carrier-phase. %to achieve centimeter-level accuracy in the ECEF frame. We also propose an algorithm for accurate GNSS-antenna-to-IMU extrinsics calibration to accurately align VIO to the ECEF frame. Together, our system achieves robust global positioning demonstrated by real-world hardware experiments in severely occluded urban canyons, and outperforms the state-of-the-art RTKLIB by a significant margin in terms of integer ambiguity solution fix rate and positioning RMSE accuracy.
arXiv.org Artificial Intelligence
Mar-2-2023
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