  In this letter, we present a robust, real-time, inertial navigation system
(INS)-Centric GNSS-Visual-Inertial navigation system (IC-GVINS) for wheeled
robot, in which the precise INS is fully utilized in both the state estimation
and visual process. To improve the system robustness, the INS information is
employed during the whole keyframe-based visual process, with strict
outlier-culling strategy. GNSS is adopted to perform an accurate and convenient
initialization of the IC-GVINS, and is further employed to achieve absolute
positioning in large-scale environments. The IMU, visual, and GNSS measurements
are tightly fused within the framework of factor graph optimization. Dedicated
experiments were conducted to evaluate the robustness and accuracy of the
IC-GVINS on a wheeled robot. The IC-GVINS demonstrates superior robustness in
various visual-degenerated scenes with moving objects. Compared to the
state-of-the-art visual-inertial navigation systems, the proposed method yields
improved robustness and accuracy in various environments. We open source our
codes combined with the dataset on GitHub
