Monocular visual guidance method for terminal docking of an autonomous underwater vehicle

Efficient recovery of the autonomous underwater vehicle (AUV) in complex underwater environments is a major technological challenge. A terminal docking method using monocular vision was presented to detect and track a circular light source marker at the docking station. To improve the recognition of the light source feature, the Canny edge detection algorithm was improved, the adaptive threshold method was used to dynamically adjust the light source contour, and the minimum enclosing circle method was used to determine the light source center when the threshold was optimal. In addition, geometric position and area constraints were used to eliminate interference from water surface reflections. For visual localization and tracking, Zhang’s calibration method was used to obtain the internal and distortion parameters of the camera, yaw and pitch errors of the AUV were estimated by comparing the light source center with the camera image center, then the position-attitude PID controller was used to achieve rapid attitude adjustment. The pool experimental results showed that the approach was simple, practical, and robust, providing a technical reference for future reliable recovery of underwater robots.