In view of the continuous technological innovation in marine engineering and the growing demand for enhanced adaptability to complex sea conditions, the binocular vision-based KCF (Kernelized Correlation Filters) algorithm is used as the target detection method based on the wave compensation device detection system. Based on the binocular vision, this method detects the load motion, capture the image feature points, calculates the position of the load in the inertial reference frame through coordinate system transformation, and monitors the spatial position and attitude of the replenished object in real time. The relative movement between the load and the replenishment ship can be eliminated by controlling the six-degree-of-freedom motion of the load, thereby achieving wave compensation. Program is developed under the Ubuntu system based on the robot operating system (ROS). Comparison and simulation are then conducted with a wave compensation prototype to validate the feasibility of the proposed detection and tracking method. The results indicate that this method is suitable for wave compensation systems.

In the civilian field, the role of maritime cargo supply is to ensure people's basic needs to be satisfied, while in the military field, the logistics support of cargo supply may affect the success or failure of local wars. An active wave compensation device installed on the crane is designed for the alongside replenishment system of two ships. The device is a nonlinear, strong coupling, multiple input and multiple output complex system for load pose control. An integral sliding-mode control strategy is proposed to optimize the controller, aiming at the improvement of the control accuracy of general sliding-mode control algorithm. By introducing an integral term, designing a new sliding-mode surface and control rate, and reasonably setting the initial state of the integrator, making the initial state of the system on the sliding surface from the beginning, thereby eliminating the arrival segment and enabling the system to quickly reach a stable state. The sliding-mode control parameters are adjusted automatically by designing fuzzy control rules to reduce the chattering of the integral sliding-mode control, and thus reducing the chattering of the system. Finally, the Lyapunov's second law is used to prove the stability of the system. The simulation experiment also demonstrates the effectiveness of the proposed control method.