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
| 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. |
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| Publication Date | 2022-04-28 |
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Myung-Il Roh, "Simulation Based Engineering for Ship and Offshore Plant", International Ocean Technology Conference & Expo (IOTCE 2015), Qingdao, China, 2015.09.01-03
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Myung-Il Roh, "Physics-based Simulation for Design, Production, and Installation of Ships and Offshore Structures", International Symposium on Computational Design and Engineering, Ho Chi Minh, Vietnam, 2017.12.13-16
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Myung-Il Roh, "Core AI Technologies for Autonomous Ships", 2023 Annual Autumn Meeting, JASNAOE (Japan Society of Naval Architects and Ocean Engineers), Nagasaki, Japan, 2023.11.27-28
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Myung-Il Roh, "Applications of Deep Learning in Ship Design, Production, and Operation Stages", Proceedings of ICDM(International Conference on Decarbonization and Digitalization in Marine Engineering) 2022, Siheung, Korea, 2022.04.28-29
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Myung-Il Roh, "SNU Education Programs for Offshore Engineering", The 30th Asian-Pacific TEAM(Technical Exchange and Advisory Meeting on Marine Structures) 2016, Mokpo, Korea, 2016.10.10.10
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Myung-Il Roh, "Introduction to Program of University Specialized for Offshore Plant Engineering in Korea", Offshore Korea 2016, Busan, Korea, 2016.10.19-20
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Modeling & Simulation II, 2016년도 한국CAD/CAM학회 동계학술발표회, 평창, 2016.01.27-29
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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
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Min-Jae Oh, Myung-Il Roh, Sung-Woo Park, Do-Hyun Chun, Jeong-Youl Lee, Myeong-Jo Son, "Operational Analysis of Container Ships Using AIS Data", Proceedings of ACDDE 2018, Okinawa, Japan, 2018.11.1-3
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Min-Jae Oh, Myung-Il Roh, Sung-Woo Park, Do-Hyun Chun, In-Il Kim, Chang-Yong Kim, Won-Joon Lee, "Estimation of Ship Energy Efficiency from Big Data Analysis", Proceedings of the 32nd Asian-Pacific TEAM 2018, Wuhan, China, pp. 262-264, 2018.10.15-18
