Online Refractive Camera Model Calibration in Visual Inertial Odometry
This addresses the problem of robust navigation in varying refractive media for underwater robotics, representing a novel method for a known bottleneck rather than an incremental improvement.
The paper tackles the problem of visual-inertial odometry in refractive fluids by proposing a general refractive camera model and online co-estimation of odometry and refractive index, enabling operation without prior knowledge or medium-specific calibration. The method was verified on underwater robot data, showing convergence to the ideal refractive index for water despite initialization perturbations and achieving on-par odometry performance.
This paper presents a general refractive camera model and online co-estimation of odometry and the refractive index of unknown media. This enables operation in diverse and varying refractive fluids, given only the camera calibration in air. The refractive index is estimated online as a state variable of a monocular visual-inertial odometry framework in an iterative formulation using the proposed camera model. The method was verified on data collected using an underwater robot traversing inside a pool. The evaluations demonstrate convergence to the ideal refractive index for water despite significant perturbations in the initialization. Simultaneously, the approach enables on-par visual-inertial odometry performance in refractive media without prior knowledge of the refractive index or requirement of medium-specific camera calibration.