Dynamic Obstacle Avoidance Control Method for Unmanned Surface Vessels Integrating Trajectory Prediction and Rule-Based Guidance

To address the challenges posed by unpredictable dynamic obstacle trajectories, rule-inconsistent avoidance behaviors, and the lack of motion feasibility in traditional path planning, this paper proposes a path planning method that integrates trajectory prediction, rule-guided avoidance, and dynamic window control. First, a lightweight traj ectory prediction framework based on polynomial curve fitting is designed. By leveraging a sliding window mechanism, the future motion trends of obstacle vessels are dynamically modeled, providing stable and reliable foresight information with low computational cost. Second, typical encounter scenarios defined in the International Regulations for Preventing Collisions at Sea (COLREGs) are incorporated to reconstruct the repulsive force direction mechanism in the Artificial Potential Field (APF) method, ensuring that avoidance behaviors comply with maritime rules and improving the rationality of avoidance directions. Finally, to address the limitations of the APF method in handling motion constraints, which often lead to excessively large avoidance angles, the Dynamic Window Approach (DW A) is introduced to ensure smoother and more feasible steering control. The predicted obstacle trajectories and the rule-compliant recommended heading are incorporated into the trajectory evaluation function, forming a closed-loop control strategy with both control feasibility and multi-objective guidance capability. Simulation and experimental results demonstrate that the proposed method not only ensures compliance with maritime rules but also reduces navigation path length by approximately 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup>, shortens sailing time by around 18.6%, and lowers the cumulative heading angle by about 23 %, thereby significantly improving path smoothness, efficiency, and obstacle avoidance practicality.