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Area of Science:

  • Maritime Navigation
  • Robotics and Autonomous Systems
  • Data Fusion

Background:

  • Collision avoidance in maritime navigation requires accurate prediction of future ship positions.
  • Current methods may lack the reliability and accuracy needed for complex scenarios.
  • Autonomous navigation systems require robust trajectory prediction capabilities.

Purpose of the Study:

  • To develop and validate a ship movement trajectory prediction algorithm.
  • To enhance the reliability and accuracy of future position predictions.
  • To integrate the algorithm into a practical navigation decision support system.

Main Methods:

  • Implementation of a data fusion algorithm.
  • Utilizing measurements from multiple, doubled autonomous positioning devices.
  • Integration into the NAVDEC (Navigation Decision Support System).

Main Results:

  • The data fusion approach significantly increases prediction reliability.
  • Enhanced accuracy in predicting ship trajectories was achieved.
  • The algorithm demonstrated practical utility in real-world maritime scenarios.

Conclusions:

  • The developed algorithm provides a reliable method for ship trajectory prediction.
  • Data fusion from multiple autonomous devices is key to improving navigational accuracy.
  • The NAVDEC system effectively incorporates this algorithm for enhanced maritime safety.