Static and dynamic multi-obstacle avoidance and docking of ASVs using computational geometry and numerical optimal control

Docking operations for autonomous surface vehicles (ASVs) involve challenges related to low-speed maneuvering in confined harbour spaces while handling environmental forces and traffic. Recently, optimization-based docking approaches have demonstrated promising results in unobstructed convex harbor areas, however they are still limited in dealing with static obstacles, which adds the significant challenge of non-convex constraints. In this paper, we present two hybrid methods that addresses the problem of docking while avoiding both static and dynamic obstacles that obstruct the direct path to the quay. The first phase involves the utilization of computational geometry for partitioning the non-convex harbor area into convex polygons. Then, a search algorithm computes the optimal sequence of convex polygons that connect the starting pose to the docking pose in an obstacle-free manner. Finally, trajectory planning is achieved via numerical optimal control. In this way, the proposed methods helps avoiding local minima and preserves the benefits of optimization-based approaches with respect to vehicle kinematics and dynamics, as well as actuator and spatial constraints.