With the progression of marine exploration and exploitation, as well as the advancements in mechanical intelligence, the utilization of the unmanned surface vehicle (USV) and the design of their guidance system have become prominent areas of focus. However, the stern ramp recovery of the USV is still in its infancy due to its unique attitude requirements and automation design. Furthermore, few studies have addressed the impact of maritime disturbances, with most research limited to simulations. To enhance the efficiency and accuracy of stern ramp recovery, this paper presents the development and construction of a novel recovery system. By incorporating physical modeling of disturbance forces acting on USVs at sea, the practicality of the system is improved. Additionally, an optimized genetic algorithm is introduced in the navigation module to improve convergence rates and subsequently enhance recovery efficiency. A line-of-sight (LOS) algorithm based on average velocity is proposed in this paper to ensure the attainment of unique attitude requirements and to improve the effectiveness of stern chute recovery. This paper provides a detailed description of the independently designed USV hardware system. Moreover, simulations and practical experiments conducted using this experimental platform are presented, offering a new solution for the USV's stern ramp recovery.
Keywords: autonomous guidance and recovery; genetic algorithm; line of sight method; path planning; stern ramp recovery; the unmanned surface vehicle.