Skip to content
Extra Form
Abstract Ships and offshore structures are constructed in a way that several units of blocks are assembled. In the block lifting process, a block is controlled indirectly through the interaction of the crane, hooks, equalizers, and wire ropes (simply, wires). Therefore, it is difficult to control the unexpected movement motions of the block accurately with several connected objects. Furthermore, it is important to construct a robust control model to cope with the modeling uncertainty of the block and the change of lug arrangement. In this study, we proposed the automatic control of the block lifting process with deep reinforcement learning (DRL), which can provide a robust control under uncertainties. The state of a block and wires, such as position, orientation and angular velocity of the block, and the lifting speed of each wire, were used as the input of DRL. Then, the lifting speed of each wire was obtained as the output action of DRL. The reward was applied to reduce the roll and pitch angle of the block and to stabilize the speed of block lifting. The proposed method was applied to various simulation examples of block lifting and compared with traditional control algorithms. As a result, it was confirmed that the proposed method could effectively control the block with unexpected motions due to the modeling uncertainty and the change of the lug arrangement.
Publication Date 2022-10-09

Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, Seung-Ho Ham, "A Method for Automatic Control of Cranes for Block Lifting in Shipyard", Proceedings of PRADS 2022, Dubrovnik, Croatia, pp. 64, 2022.10.09-13


  1. 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
  2. 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
  3. 송하민, 노명일, 김기수, "함정의 전투 시나리오를 고려한 승조원 운영 최적화" 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12

    CategoryDomestic Conference
    Read More
  4. 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
  5. 정동근, 노명일, 김기수, 이준식, 김대혁, 장왕석, "요트 전용의 연안 항해 프로그램 개발", 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12

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

    CategoryDomestic Conference
    Read More
  7. 여인창, 노명일, 전도현, "선박 배관망 지지대의 최적 배치 설계", 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12

    CategoryDomestic Conference
    Read More
  8. 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 2022, Siheung, Korea, 2022.04.28-29

    CategoryInternational Conference
    Read More
  9. 박정호, 노명일, 이혜원, 하지상, 조영민, 손남선, "다중 선박으로부터의 카메라 영상 기반 단일 해상 장애물의 탐지 및 추적 방법", 2022년도 한국CDE학회 동계학술발표회, 제주, 2022.02.09-12

    CategoryDomestic Conference
    Read More
  10. Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, "Deep Reinforcement Learning-Based Ship Collision Avoidance Considering Collision Risk", Proceedings of TEAM 2022, Istanbul, Turkey, pp. 268, 2021.12.06-07

    CategoryInternational 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