Automatic Berthing

Automatic berthing systems aim to automate the complex process of docking ships, improving efficiency and safety. Current research focuses on developing robust control algorithms, employing techniques like reinforcement learning (including Proximal Policy Optimization and Deep Deterministic Policy Gradient variants), evolutionary strategies (such as Covariance Matrix Adaptation Evolution Strategy), and adaptive large neighborhood search heuristics to optimize berthing maneuvers under various conditions and uncertainties. These advancements address challenges in data acquisition and computational complexity, offering potential for significant improvements in port operations and autonomous vessel navigation.