Adaptive Sensor Fusion of Camera, GNSS and IMU for Autonomous Driving Navigation

The Visual-Inertial navigation system(VINS) has become a popular navigation approach in the field of unmanned aerial vehicles(UAV) or robotics. While its performance under autonomous driving scenario is not satisfactory due to the fact that autonomous driving scenario is more challenging and dynamic than the UAV scenario. Thus, the Visual-Inertial navigation system will collapse occasionally and thus undermine the navigation result. In this work, we propose a adaptive mechanism that could switch between three modes, only VINs, only GNSS and VINS&GNSS fusion. When Visual-Inertial component breaks down, our algorithm could only rely on the GNSS signal until VINS recovers. Similarly, when GNSS signal is not very accurate, our system could only rely on the VINS-Mono. We demonstrate our algorithm under challenging scenarios such as night sight and high speed road and do both qualitative analysis and quantitative analysis.