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In this letter, we present a robust, real-time, inertial navigation system(INS)-Centric GNSS-Visual-Inertial navigation system (IC-GVINS) for wheeledrobot, in which the precise INS is fully utilized in both the state estimationand visual process. To improve the system robustness, the INS information isemployed during the whole keyframe-based visual process, with strictoutlier-culling strategy. GNSS is adopted to perform an accurate and convenientinitialization of the IC-GVINS, and is further employed to achieve absolutepositioning in large-scale environments. The IMU, visual, and GNSS measurementsare tightly fused within the framework of factor graph optimization. Dedicatedexperiments were conducted to evaluate the robustness and accuracy of theIC-GVINS on a wheeled robot. The IC-GVINS demonstrates superior robustness invarious visual-degenerated scenes with moving objects. Compared to thestate-of-the-art visual-inertial navigation systems, the proposed method yieldsimproved robustness and accuracy in various environments. We open source ourcodes combined with the dataset on GitHub

IC-GVINS: A Robust, Real-time, INS-Centric GNSS-Visual-Inertial Navigation System for Wheeled Robot