Environment Driven Underwater Camera-IMU Calibration for Monocular Visual-Inertial SLAM

Most state-of-the-art underwater vision systems are calibrated manually in shallow water and used in open seas without changing. However, the refractivity of the water is adaptively changed depending on the salinity, temperature, depth or other underwater environmental indexes, which inevitably generate the calibration errors and induces incorrectness e.g., for underwater Simultaneously Localization and Mapping (SLAM). To address this issue, in this paper, we propose a new underwater Camera-Inertial Measurement Unit (IMU) calibration model, which just needs to be calibrated once in the air, and then both the intrinsic parameters and extrinsic parameters between the camera and IMU could be automatically calculated depending on the environment indexes. To our best knowledge, this is the first work to consider the underwater Camera-IMU calibration via environmental indexes. We also build a verification platform to validate the effectiveness of our proposed method on real experiments, and use it for underwater monocular Visual-Inertial SLAM.