Design and preliminary results of novel situational awareness system for autonomous ship based on artificial intelligence techniques

被引:0
作者
Choi H.-T. [1 ]
Park J. [1 ]
Choi J. [1 ]
Kang M. [1 ]
Lee Y. [2 ]
Jung J. [1 ]
Kim J. [3 ]
Kweon H. [3 ]
Kim J. [3 ]
Yoon K.-J. [3 ]
Kim H. [4 ]
Park S.-T. [5 ]
机构
[1] Autonomous & Intelligent Maritime Systems Research Division, Korea Research Institute of Ships and Ocean Engineering (KRISO)
[2] Marine System Research Division, KRISO
[3] Department of Mechanical Engineering, KAIST
关键词
Autonomous ship; Bayesian estimation; Collision risk; Deep-learning; Object detection; Situational awareness;
D O I
10.5302/J.ICROS.2021.21.0063
中图分类号
学科分类号
摘要
With recent advancements in artificial intelligence technologies, the academia and industry have heightened performance expectations when designing autonomous ships, and major ship building companies and governments have been conducting large-scale research projects around the world. This paper proposes a novel design concept, and presents the key features and preliminary results of a situational awareness system for autonomous ships, named the iSAS (Intelligent Situational Awareness System), and is being developed as part of the Korea Autonomous Surface Ships (KASS) project launched in April 2020. The iSAS comprises deep-learning algorithms for detecting marine objects using camera, radar, and LiDAR (Light Detection and Ranging), a probabilistic-based data association and tracking algorithm and a new collision risk evaluation method. Because the iSAS estimates motions of all and each objects along with their semantic information, it could not be said as a simple replacement of what the captain does. By sequentially installing the iSAS on a small test ship and a demonstration ship during the project, we will simultaneously perform algorithm development and field verification to achieve reliability in the real environment. The iSAS can be used not only for autonomous ships but also for manned ships to enhance safety and reduce costs in the near future. © ICROS 2021.
引用
收藏
页码:556 / 564
页数:8
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