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Abstract The block erection using a crane such as a gantry crane and a floating crane is one of the most important processes in the production of ships and offshore structures. To mount the block with the correct position and angle, it is important to control the block accurately not to occur the unexpected movement like rotation. However, it is difficult to apply the existing control theory to the block lifting operation because the movement of the block is controlled indirectly with the control of various objects such as the crane and wire ropes. To solve this problem, a block control method based on deep reinforcement learning is proposed in this study. The proposed method is easier to control the block with wire ropes and to consider irregular external force than existing control theory. In this study, the angle and angular velocity of the lifting block and the hoisting speed of each wire rope that can affect the motion of the block are set as states of reinforcement learning, and the hoisting speed that is the control object is set as an action of reinforcement learning. The reward function of reinforcement learning is designed to increase when the angle of the block decrease and the speed of the block is close to the target speed. In this study the policy gradient method which is a kind of policy-based methods of deep reinforcement learning is used to solve the problem with continuous states and action. To check the applicability and feasibility of the proposed method, The block lifting simulation is performed using the existing control theory and the proposed method. We compared the proposed method with the existing control theory. The result shows that the proposed method can minimize the motion of the lifting block more effectively than the existing control theory.
Publication Date 2019-08-28

Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, Seung-Ho Ham, "A Crane Movement Control for Stability of Block Erection Based on Deep Reinforcement Learning", MIM(International Federation of Automatic Control) 2019, Berlin, Germany, 2019.08.28-30


List of Articles
번호 분류 제목 Publication Date
103 International Conference Hye-Won Lee, Myung-Il Roh, Seung-Ho Ham, "Control of the Underactuated Gantry Crane for the Block Erection Operation in the Shipyard", MIM 2019, Berlin, Germany, 2019.08.28-30 file 2019-08-29
102 International Conference Jong-Hyeok Lee, Myung-Il Roh, Jin-Hyeok Kim, Sung-Jun Lee, Seung-Ho Ham, "Development of a Ship Navigation Simulator Based on Digital Twin Technology", Proceedings of ACDDE 2019, Penang, Malaysia, pp. 245, 2019.07.07-10 file 2019-07-08
101 Conference Chairman 설계 및 법규 1 (A3), 2019년도 한국해양공학회 춘계학술발표회, 제주, 2019.05.15-17 2019-05-16
100 Conference Chairman Session 7 (Ship & Ocean Engineering), 2019년도 한국CDE학회 학술발표회, 횡성, 2019.01.23-26 2019-01-24
99 International Conference Sung-Jun Lee, Myung-Il Roh, Min-Jae Oh, Youngsoo Seok, Won-Jae Lee, June-Beom Lee, Hyun Soo Kim, "Image-based Object Detection and Tracking Method for Ship Navigation," Proceedings of ICCAS 2019, Rotterdam, Netherlands, pp. 89-92, 2019.09.24-26 file 2019-09-24
98 International Conference Min-Jae Oh, Myung-Il Roh, Young-Soo Seok, and Sung-Jun Lee, "Optimization of a Ship Hull Form using Deep Learning", Proceedings of ACDDE 2019, Penang, Malaysia, 2019.07.07-10 file 2019-07-08
97 International Conference Do-Hyun Chun, Myung-Il Roh, Seung-Ho Ham, Hoon-Kyu Oh, Sang-Ok Lee, "Optimum Layout Design of Wedges of Panel for an LNG Tank Considering Amount of Resin Ropes", Proeedings of ISOPE 2019, Honolulu, Hawaii, pp. 1289-1292, 2019.06.16-21 file 2019-06-19
» International Conference Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, Seung-Ho Ham, "A Crane Movement Control for Stability of Block Erection Based on Deep Reinforcement Learning", MIM 2019, Berlin, Germany, 2019.08.28-30 file 2019-08-28
95 Domestic Conference 오민재, 노명일, 김범수, 김용환, "선박의 운항 효율을 고려한 선형 변환 방법", 2019년도 대한조선학회 추계학술발표회, 경주, pp. 480, 2019.10.24-2019.10.25 file 2019-10-24
94 Domestic Conference 노명일, "스마트 함정의 구현을 위한 설계 기술 연구", 함정기술연구회 하계연구발표회, 진해, 2019.07.18-19 2019-07-18
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