Skip to content
Extra Form
Abstract Autonomous ships require an awareness system to recognize surrounding obstacles during navigation. In general, the awareness system uses data obtained by sensors such as RADAR (RAdio Detection And Ranging) and AIS (Automatic Identification System). However, autonomous ships operating in the marine environment should recognize small obstacles, including buoys that cannot be detected by RADAR and boats without the AIS system. Just as the tracking accuracy is improved by the fusion of sensors with different characteristics, a camera with a wide-angle of view or a camera capable of night detection can complement each other. In addition, tracking accuracy can be further improved if camera images from multiple viewpoints can be used in the case of detection through multiple ships. Therefore, in this study, camera-based detection and tracking methods were developed to be aware of marine obstacles that could not be recognized by RADAR or AIS. Firstly, the Convolutional Neural Network (CNN) based YOLO v5 model, combined with an attention module, was suggested for obstacle detection. Subsequently, the position and speed of the detected obstacles were tracked using the extended Kalman Filter. Finally, the tracks of the obstacles from various cameras mounted on multiple ships were integrated using the sensor fusion method to increase the accuracy. The field tests were conducted with a USV (Unmanned Surface Vessel) for various ship encountering scenarios to verify the developed methods in the actual marine environment. As a result, it was confirmed that stable and accurate detection and tracking of marine obstacles was performed using multiple cameras.
Publication Date 2022-04-28

Jeong-Ho Park, Myung-Il Roh, Hye-Won Lee, Jisang Ha, Yeong-Min Jo, Nam-Sun Son, "Detection and Tracking Methods of Maritime Obstacles Using Multiple Cameras", Proceedings of ICDM(International Conference on Decarbonization and Digitalization in Marine Engineering) 2022, Siheung, Korea, 2022.04.28-29


  1. 조영민, 노명일, 이혜원, 유동훈, "선박 탐지를 위한 레이더 데이터의 처리 방법", 2022년도 대한조선학회 춘계학술발표회, 제주, pp. 308, 2022.06.02-04

    CategoryDomestic Conference
    Read More
  2. 전도현, 노명일, 여인창, "LNG선 멤브레인 탱크의 최적 설계 방법", 2022년도 대한조선학회 춘계학술발표회, 제주, pp. 411, 2022.06.02-04

    CategoryDomestic Conference
    Read More
  3. Jeong-Ho Park, Myung-Il Roh, Hye-Won Lee, Jisang Ha, Yeong-Min Jo, Nam-Sun Son, "Obstacle Detection and Tracking of Unmanned Surface Vehicles Using Multi-view Images in Marine Environment", Proceedings of ICCAS 2022, Yokohama, Japan, 2022.09.13-15

    CategoryInternational Conference
    Read More
  4. Dong-Guen Jeong, Myung-Il Roh, Ki-Su Kim, Jun-Sik Lee, Dae-Hyuk Kim, Wang-Seok Jang, "A Route Planning Method for Coastal Navigation of Small Ships", Proceedings of ICCAS 2022, Yokohama, Japan, pp. 153-156, 2022.09.13-15

    CategoryInternational Conference
    Read More
  5. Min-Chul Kong, Myung-Il Roh, Ki-Su Kim, Jongoh Kim, Hogyun Park, Jeongyoul Lee, "A Method of Variable Recognition and Connection for Reviewing Ship Regulations", Proceedings of ICCAS 2022, Yokohama, Japan, pp. 171-175, 2022.09.13-15

    CategoryInternational Conference
    Read More
  6. Hye-Won Lee, Myung-Il Roh, Seung-Ho Ham, Bo-Woo Nam, "Coupled Analysis of the LNG Offloading Operation Based on Multibody Dynamics", Proceedings of PRADS 2022, Dubrovnik, Croatia, 2022.10.09-13

    CategoryInternational Conference
    Read More
  7. 송하민, 노명일, 김기수, "함정의 전투 시나리오를 고려한 승조원 운영 최적화" 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12

    CategoryDomestic Conference
    Read More
  8. 이혜원, 노명일, 김예린, "조선소의 블록 리프팅을 위한 모델 예측 제어 기반 크레인 시뮬레이션", 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12

    CategoryDomestic Conference
    Read More
  9. 정동근, 노명일, 김기수, 이준식, 김대혁, 장왕석, "요트 전용의 연안 항해 프로그램 개발", 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12

    CategoryDomestic Conference
    Read More
  10. 전도현, 노명일, 이혜원, 함승호, "블록의 특성을 고려한 크레인의 와이어 제어 방법", 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12

    CategoryDomestic Conference
    Read More
Board Pagination Prev 1 2 3 4 5 6 7 8 9 10 ... 46 Next
/ 46

Powered by Xpress Engine / Designed by Sketchbook

sketchbook5, 스케치북5

sketchbook5, 스케치북5

나눔글꼴 설치 안내


이 PC에는 나눔글꼴이 설치되어 있지 않습니다.

이 사이트를 나눔글꼴로 보기 위해서는
나눔글꼴을 설치해야 합니다.

설치 취소