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Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous

Jolanta Koszelew1, Joanna Karbowska-Chilinska1, Krzysztof Ostrowski1

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Summary

This study introduces a multi-surface vehicle beam search algorithm (MBSA) for autonomous ships to generate safe anti-collision trajectories in complex, many-to-many encounters. The MBSA effectively addresses multi-vessel navigation challenges in open seas.

Keywords:
anti-collision trajectoriesautonomous surface vehiclebeam search algorithm (BSA)many-to-many encounter situationmulti-surface vehicle beam search algorithm (MBSA)

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Area of Science:

  • Maritime Navigation
  • Robotics
  • Artificial Intelligence

Background:

  • Autonomous ships require advanced collision avoidance systems for safe operation.
  • Multi-vessel encounter situations present complex trajectory planning challenges distinct from single-vessel scenarios.

Purpose of the Study:

  • To address the problem of anti-collision trajectory planning in many-to-many encounter situations for autonomous surface vehicles.
  • To propose and evaluate a novel algorithm for safe multi-vessel navigation.

Main Methods:

  • Development of the multi-surface vehicle beam search algorithm (MBSA).
  • Adaptation of the beam search algorithm (BSA) for one-to-many encounter solutions.
  • Testing MBSA with simulated data for performance evaluation.

Main Results:

  • The MBSA effectively plans anti-collision trajectories in complex many-to-many scenarios.
  • The algorithm builds upon proven one-to-many encounter solutions.
  • Simulated data validated the MBSA's capability in multi-vessel situations.

Conclusions:

  • The MBSA offers a viable solution for autonomous ship collision avoidance in multi-vessel encounters.
  • This algorithm is crucial for the advancement of autonomous shipping.
  • Further research can integrate Collision Regulations (COLREGs) and vehicle dynamics into the MBSA.