GVINS: Tightly Coupled GNSS–Visual–Inertial Fusion for Smooth and Consistent State Estimation

Visual–inertial odometry (VIO) is known to suffer from drifting, especially over long-term runs. In this article, we present GVINS, a nonlinear optimization-based system that tightly fuses global navigation satellite system (GNSS) raw measurements with visual and inertial information for real-time and drift-free stateestimation. Our system aims to provide accurate global six-degree-of-freedom estimation under complex indoor–outdoor environments, where GNSS signals may be intermittent or even inaccessible. To establish the connection between global measurements and local states, a coarse-to-fine initialization procedure is proposed to efficiently calibrate the transformation online and initialize GNSS states…