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Abstract The block erection using a gantry crane is an important process for the production of the ships in a shipyard. The motion of the block should be controlled accurately under the external forces to prevent collision with the structures and the excessive loads on wire ropes. However, it is difficult to control the block during the lifting because the movement of the block is indirectly controlled with various objects such as trolleys, hooks, equalizers, and wire ropes. Therefore, we proposed the Deep Reinforcement Learning (DRL)-based block lifting method in this study. The DRL-based block lifting method can control the block under the change of the center of gravity and modelling uncertainty. Furthermore, the DRL-based block lifting method can provide robust control with an unexpected motion of the block due to the unexpected external disturbance. The position, orientation and angular velocity of the block and hoisting speed of wire ropes were set as the input state of the neural network of DRL. The hosting speed of wire ropes was controlled as the output action of DRL. The functions to minimize the change of orientation and to stabilize the speed of the block were set as the reward of DRL. In this study, the deep deterministic policy gradient (DDPG) method of DRL, which is a kind of off-policy actor-critic method, was applied to solve the problem with continuous state space and continuous multi-action space. To verify the DRL-based block lifting method proposed in this study, it was compared with traditional control algorithms for various simulation examples. As a result, the proposed method could effectively control the block with the modelling uncertainty. Also, the proposed method could respond to the unexpected motion of the block effectively due to the unexpected external disturbance.
Publication Date 2022-04-28

Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, Seung-Ho Ham, "A Block Lifting Method with Wire Ropes Based on Deep Reinforcement Learning", Proceedings of ICDM(International Conference on Decarbonization and Digitalization in Marine Engineering) 2022, Si-Heung, Korea, 2022.04.28-29


List of Articles
번호 분류 제목 Publication Date
446 International Conference Do-Hyun Chun, Myung-Il Roh, In-Chang Yeo, "Optimum Design of Membrane-type LNG Tanks for Installing Insulation", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10 2022-11-07
445 Domestic Conference 박정호, 노명일, 이혜원, 조영민, 손남선, "영상 기반의 선박 추적을 위한 개선된 방법", 2022년도 대한조선학회 춘계학술발표회, 제주, p.311, 2022.06.02-04 file 2022-06-02
444 Domestic Conference 김진혁, 노명일, 여인창, 김기수, 오민재, "딥 러닝을 이용한 소형 선박의 저항 예측", 2022년도 대한조선학회 춘계학술발표회, 제주, pp. 290, 2022.06.02-04 file 2022-06-02
443 International Conference Dong-Guen Jeong, Myung-Il Roh, Ki-Su Kim, Jun-Sik Lee, Dae-Hyuk Kim, Wang-Seok Jang, "A Method for Route Planning of Small Ships in Coastal Areas", Proceedings of ICDM 2022, Si-Heung, Korea, 2022.04.28-29 2022-04-28
» International Conference Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, Seung-Ho Ham, "A Block Lifting Method with Wire Ropes Based on Deep Reinforcement Learning", Proceedings of ICDM 2022, Si-Heung, Korea, 2022.04.28-29 2022-04-28
441 Domestic Conference 이혜원, 노명일, 박정호, "선박 추적을 위한 센서 데이터 연관 방법", 2022년도 대한조선학회 춘계학술발표회, 제주, pp. 309, 2022.06.02-04 file 2022-06-02
440 Domestic Conference 여인창, 노명일, 전도현, 장석호, 허재원, "안전성과 경제성을 고려한 배관 지지대 설계", 2022년도 대한조선학회 춘계학술발표회, 제주, p. 403, 2022.06.02-04 file 2022-06-02
439 Domestic Conference 공민철, 노명일, 김기수, 김종오, 박호균, 김주성, "PDF 문서 내 변수 인식 및 가시화 프로그램 개발", 2022년도 대한조선학회 춘계학술발표회, 제주, p. 198, 2022.06.02-04 file 2022-06-02
438 International Conference In-Chang Yeo, Myung-Il Roh, Hye-Won Lee, "An Optimization Method of the Surround-View Camera System for Automatic Berthing of Ships", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10 2022-11-06
437 International Conference Min-Chul Kong, Myung-Il Roh, Jisang Ha, Jeong-Ho Park, EunSeok Jin, Donghun Yu, "Integrated Navigation Assistance System Using Augmented Reality", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10 2022-11-09
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