Automated AUV docking control with light-field imaging

An automated docking system is presented for an autonomous underwater vehicle utilizing light-field imaging for navigation guidance. This article focuses on three major components of the system: docking position acquisition with light-field imaging, optimal docking trajectory planning, and nonlinear trajectory tracking control. With the camera sensor data of each photographic exposure, depth maps of the scene are generated through light-field tomographic reconstruction to provide relative position update of the docking station. A variational approach is adopted to optimize the resulting depth maps for improved guidance accuracy. Assisted by color detection, target docking positions for the vehicle are generated based on the knowledge of the docking structure, the depth maps, and the extrinsic camera calibration matrix. A nonlinear optimal trajectory generator is then used to calculate the best docking trajectory by solving the nonlinear programing problem that simultaneously minimizes the mission time and actuation energy. Asymptotic trajectory tracking performance is achieved through a continuous, feedback control designed based on the robust integral of the sign of the error. Uniform, time-invariant background flows are considered in optimal trajectory planning and trajectory tracking control design to generalize the proposed docking control method for missions with ocean currents or docking structures in regulated motions.