IC-GVINS: A Robust, Real-Time, INS-Centric GNSS-Visual-Inertial Navigation System
Xiaoji Niu, Hailiang Tang, Tisheng Zhang, Jing Fan, Liu Jingnan
Abstract
Visual navigation systems are susceptible to complex environments, while inertial navigation systems (INS) are not affected by external factors. Hence, we present IC-GVINS, a robust, real-time, INS-centric global navigation satellite system (GNSS)-visual-inertial navigation system to fully utilize the INS advantages. The Earth rotation has been compensated in the INS to improve the accuracy of high-grade inertial measurement units (IMUs). To promote the system robustness in high-dynamic conditions, the precise INS information is employed to assist the feature tracking and landmark triangulation. With a GNSS-aided initialization, the IMU, visual, and GNSS measurements are tightly fused in a unified world frame within the factor graph optimization framework. Dedicated experiments were conducted in the public vehicle and private robot datasets to evaluate the proposed method. The results demonstrate that IC-GVINS exhibits superior robustness and accuracy in complex environments. The proposed method with the INS-centric architecture yields improved robustness and accuracy compared to the state-of-the-art methods. We open-source the proposed IC-GVINS and the multisensor datasets on GitHub (https://github.com/i2Nav-WHU/IC-GVINS).