Guaranteed collision avoidance for autonomous surface vehicles equipped with a LiDAR using a CLF-CBF-QP controller

Safe autonomous navigation in marine environments remains challenging due to the need to simultaneously handle multiple dynamic obstacles, uncertain conditions, and the inherent complexity of vessel dynamics while maintaining both stability and safety guarantees. This paper introduces a High-Order Barrier Function and Control Lyapunov Function (HOBF-CLF) based controller for Autonomous Surface Vehicles navigating unknown environments. Using real-time LiDAR data and a clustering algorithm, the controller efficiently handles multiple obstacles by treating them as separate entities. The HOBF-CLF approach guarantees both safety and stability through real-time quadratic optimization. Simulations show it performs better when compared to a state-of-the-art Model Predictive Controller and some PID-based methods in terms of control effort and computational efficiency.