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Abstract For safe operation, a navigator needs to accurately recognize the circumstance around the ship and constantly focus on objects that require attention. Therefore, the navigator should properly utilize the information of the field of vision seen from the ship and the sensor data such as AIS (Automatic Identification System), RADAR (RAdio Detection And Ranging), etc. However, since such data have different dimensions and meanings, it is not easy to interpret except for professionals, and it is not intuitive. In addition, it is difficult to obtain consistent and high-accuracy data depending on the characteristics of each sensor (detection distance, detection period, error, blind spot, etc.) and whether other ships are equipped with the AIS system. Therefore, we developed an integrated navigation assistance system that can effectively report sensor data to the navigator by sensor data fusion. We tracked the positions of ships by sensor data fusion through the tracking filter. To supplement the limitations of sensors, we used the object detection model. Collision risk was quantitatively calculated using the detected ships and tracking data, and the collision-free path of the own ship was generated. The above processes were modularized and integrated, and communication packets were defined to enable data exchange between each module. Finally, we implement a navigation assistance system that efficiently provides necessary information for navigating using AR (Augmented Reality) technology. In addition to ship detection and tracking data, the ship needs to visualize its own sensor data, such as rudder angle and engine RPM. Various data was provided as an intuitive UI by appropriately overlapping the information within the image. The integrated navigation assistance system was mounted on a test ship in actual operation, and its effectiveness was confirmed by transmitting necessary information to the land command center.
Publication Date 2022-11-09
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

  1. 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

  2. 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

  3. 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

  4. 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

  5. Min-Jae Oh, Myung-Il Roh, "Hull Form Surface Generation Using T-Spline", Proceedings of the 31st Asian-Pacific TEAM 2017, Osaka, Japan, 2017.09.25-28

  6. 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

  7. Min-Chul Kong, Myung-Il Roh, Jisang Ha, Mijin Kim, Jeoungyoun Kim, "A Method for the Generation of Optimal Patterns for Equipment Unit Modules in the Engine Room", Proceedings of 10th PAAMES and AMEC 2023, Kyoto, Japan, 2023.10.18-20

  8. No Image 30Mar
    by SyDLab
    in 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

  9. Min-Chul Kong, Myung-Il Roh, Jisang Ha, Eun Seok Jin, Donghun Yu, "Design of the Integrated System for the Safe Operation Based on Augmented Reality", Proceedings of PRADS 2022, Dubrovnik, Croatia, 2022.10.09-13

  10. Min-Chul Kong, Myung-Il Roh, In-Chang Yeo, Ki-Su Kim, Jeongyoul Lee, Jongoh Kim, Gapheon Lee, "A Detection Method of Objects with Text in Drawings Based on Deep Learning", Proceedings of ISOPE 2023, Ottawa, Canada, 2023.06.19-23

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