In this work we propose a solution to the Unmanned Surface Vessels (USV) path-following problem by suggesting an improved model predictive control (MPC) based on global course constraint (GCC) and event-triggered mechanism (ETM). The designed GCC guidance law incorporates the LOS concept and overcomes its lack of reference signal near the waypoint. The developed MPC controller involves an ETM that ultimately optimizes the deviation according to its prediction ability and effect on energy saving. We challenge our model against current methods on the evaluation platform vessel “Yukun” of Dalian Maritime University and demonstrate the effectiveness and superiority of the suggested path-following algorithm over existing methods.

Trajectory planning aims to provide a time-related control target that contains the concerned states. For an underactuated surface vehicle (USV), planning challenges include limitations on curvature, speed, acceleration, and jerk. These challenges are relevant for the precise control of USVs. To solve these problems, an on-line double S method and multi-scale A* trajectory planning algorithm is proposed by integrating Reeds–Shepp curves (RSC), where a quad-tree-based graph is used for path planning and collision detection. Simulations illustrate that the proposed method has a better performance than the smooth rapid-exploration random tree (smooth-RRT) method and jump point search (JPS) method, and that path length and the state limitations are satisfied.

Theta* algorithm is a searching-based path planning algorithm that gives an optimal path with more flexibility on route angle than A* method. The dynamics of USV is characterized by large inertia, so that larger turning angle is preferred. In view of the shortcomings of traditional Theta* algorithm, such as being hard to balance overall situation and details in long-distance planning, and lacking of waypoint replacement scheme when a waypoint is unreachable, it is inappropriate to make long-distance planning through Theta* algorithm directly. In order to ensure safe navigation for unmanned surface vehicle (USV), this paper proposes a multi-scale Theta* algorithm to solve these defects. Simulation result manifests the proposed scheme can provide a path clear of obstacles with several fold reduction in time consumption. The proposed planning method simplifies path planning process and contributes to the development of marine transportation.