Ship docking simulations have become a valuable tool in maritime operations, offering a wide range of applications from training and risk assessment to the development of autonomous berthing systems for autonomous and semi-autonomous ship operations. Precise and quick control and decision-making are essential for the latter. The primary aim of this study is to create a practical tool and calculation methodology that serves as an efficient alternative to CFD, enabling rapid simulations for ship maneuvering applications, particularly in fundamental docking scenarios. The tested maneuvers are straight-ahead motion, crash-ahead motion, turning and kicking turn at slow speed. The monitored ship’s velocity and position during its move is validated using experimental and numerical data from the literature, ensuring its accuracy and reliability. The results demonstrate that the proposed methodology is capable of making highly accurate maneuvering predictions, thus providing fast and reliable data for learning algorithms that will govern docking operations.

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Fundamental Study on Forecasting Surface Ship Maneuvering Characteristics for Autonomous Docking Operations

  • Hasan Timurlek,
  • Mahmutcan Esenkalan,
  • Taner Cosgun

摘要

Ship docking simulations have become a valuable tool in maritime operations, offering a wide range of applications from training and risk assessment to the development of autonomous berthing systems for autonomous and semi-autonomous ship operations. Precise and quick control and decision-making are essential for the latter. The primary aim of this study is to create a practical tool and calculation methodology that serves as an efficient alternative to CFD, enabling rapid simulations for ship maneuvering applications, particularly in fundamental docking scenarios. The tested maneuvers are straight-ahead motion, crash-ahead motion, turning and kicking turn at slow speed. The monitored ship’s velocity and position during its move is validated using experimental and numerical data from the literature, ensuring its accuracy and reliability. The results demonstrate that the proposed methodology is capable of making highly accurate maneuvering predictions, thus providing fast and reliable data for learning algorithms that will govern docking operations.