Objective This study addresses the critical challenge of precise waypoint tracking for an underactuated Unmanned Surface Vehicles (USV) in complex marine environments. The primary objective is to integrate path planning with guidance and control to enhance tracking accuracy, ensure system reliability, and optimize overall performance. The research aims to provide a robust and efficient solution for autonomous USVs, which are essential for various maritime missions, including environmental monitoring, resource exploration, search-and-rescue operations, and military applications.

Method This study proposes a control framework named NRRT-FTC (Non-Uniform Rational B-Spline-Based Rapidly Exploring Random Tree Fault-Tolerant Control), designed to improve path planning and waypoint tracking for USVs. First, the framework utilizes an improved Rapidly Exploring Random Tree (RRT) algorithm to efficiently select waypoints and remove redundant points from the path. The waypoints are then fitted using Non-Uniform Rational B-Splines (NURBS), a powerful technique that ensures the generation of a smooth and accurate path passing through all the waypoints. This NURBS-based approach not only optimizes the smoothness of the generated path but also enhances the controllability and feasibility of the trajectory, making it suitable for practical applications in marine environments. Furthermore, the NRRT-FTC framework incorporates a fault-tolerant control strategy based on finite-time observers. This strategy plays a critical role in managing environmental disturbances, system uncertainties, and actuator failures. By performing real-time state estimation and adjusting the control inputs accordingly, the framework ensures that the USV can continue to track the planned path accurately, even under failure conditions. This design improves system robustness and ensures reliable performance under diverse operational scenarios.

Results Simulation experiments were conducted to validate the effectiveness of the NRRT-FTC framework. The experimental results demonstrated significant improvements in both path planning and tracking control compared to other methods. Specifically, the control error was reduced by 31.78%, control efficiency increased by 16.65%, and task execution efficiency was improved by 36.17%. The NRRT-FTC framework also demonstrated strong resilience to environmental disturbances and actuator faults, ensuring precise waypoint tracking even under adverse conditions including wind, waves, and sensor noise.

Conclusion The NRRT-FTC framework significantly improves the waypoint tracking accuracy of underactuated USVs, thereby enhancing system robustness and reliability. By integrating path planning and guidance control, the framework provides a practical solution for precise navigation in marine missions, particularly in challenging and unpredictable environments. The findings contribute to USV autonomy, providing a robust theoretical foundation for future advancements in autonomous vehicle technology for maritime applications. The proposed approach has significant potential for real-world applications, including autonomous navigation in complex marine environments and beyond.