한국군사과학기술학회지 (Journal of the Korea Institute of Military Science and Technology)

  • 제27권6호
  • /
  • Pages.677-683
  • /
  • 2024
  • /
  • 1598-9127(pISSN)
  • /
  • 2636-0640(eISSN)
한국군사과학기술학회 (The Korea Institute of Military Science and Technology)
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회전익 항공기의 착함을 위한 이미지 기반 함정 자세 예측

An Image-based Ship Attitude Estimation Method for Helicopter Landing

  • 박건하 (해군사관학교 기계시스템공학과) ;
  • 정성훈 (해군사관학교 기계시스템공학과)
  • Geonha Park (Department Mechanical System Engineering, Republic of Korea Naval Academy) ;
  • Sunghoon Jung (Department Mechanical System Engineering, Republic of Korea Naval Academy)
  • 투고 : 2024.07.24
  • 심사 : 2024.09.28
  • 발행 : 2024.12.05
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초록

Landing a helicopter on a moving ship requires accounting for the ship's attitude. However, it is not only challenging to visually assess the ship's attitude, but it also creates illusions for the pilot, increasing the risk of accidents. In this study, we propose an image-based ship attitude estimation method to assist helicopter landings. The proposed method enhances landing safety by predicting the ship's heave, pitch, and roll using only helicopter-mounted optical devices and pre-trained deep learning models, without requiring communication with the ship. To implement this approach, we generated a dataset by simulating a virtual sea environment and ship motion. Using this data, we trained deep learning models to predict the ship's attitude based solely on images. Experimental results confirm the feasibility of the proposed method, with VGG-16 demonstrating particularly effective attitude prediction under simulated conditions.

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참고문헌

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