Monocular Visual-Inertial Fusion With Online Initialization And Camera-Imu Calibration

There have been increasing demands in developing micro aerial vehicles with vision-based autonomy for search and rescue missions in complex environments. In particular, the monocular visual-inertial system (VINS), which consists of only an inertial measurement unit (IMU) and a camera, forms a great lightweight sensor suite due to its low weight and small footprint. In this work, we address two challenges for rapid deployment of monocular VINS - the initialization problem and the calibration problem. We propose a methodology that is able to initialize velocity, gravity, visual scale, and camera-IMU extrinsic calibration on-the-fly. Our approach does not require any prior knowledge about the mechanical configuration of the system. It is a significant step towards plug-and-play and highly customizable visual navigation for mobile robots. We show through online experiment that our method leads to accurate calibration of camera-IMU transformation with errors of 0.02 m in position and 2 degrees in rotation.