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智能船舶远程驾驶控制技术研究现状与趋势

王远渊 刘佳仑 马枫 王兴平 严新平

王远渊, 刘佳仑, 马枫, 等. 智能船舶远程驾驶控制技术研究现状与趋势[J]. 中国舰船研究, 2021, 16(1): 18–31 doi: 10.19693/j.issn.1673-3185.01939
引用本文: 王远渊, 刘佳仑, 马枫, 等. 智能船舶远程驾驶控制技术研究现状与趋势[J]. 中国舰船研究, 2021, 16(1): 18–31 doi: 10.19693/j.issn.1673-3185.01939
WANG Y Y, LIU J L, MA F, et al. Review and prospect of remote control intelligent ships[J]. Chinese Journal of Ship Research, 2021, 16(1): 18–31 doi: 10.19693/j.issn.1673-3185.01939
Citation: WANG Y Y, LIU J L, MA F, et al. Review and prospect of remote control intelligent ships[J]. Chinese Journal of Ship Research, 2021, 16(1): 18–31 doi: 10.19693/j.issn.1673-3185.01939

智能船舶远程驾驶控制技术研究现状与趋势

doi: 10.19693/j.issn.1673-3185.01939
基金项目: 国家重点研发计划资助项目(2018YFB1601503,2018YFB1601505);工信部高技术船舶科研项目(2018473);国家自然科学基金资助项目(51709217)
详细信息
    作者简介:

    王远渊,男,1988年生,博士

    刘佳仑,男,1987年生,博士,副研究员

    马枫,男,1985年生,博士,副研究员,硕士生导师

    王兴平,男,1980年生,硕士

    严新平,男,1959年生,博士,教授,博士生导师,中国工程院院士

    通信作者:

    刘佳仑

  • 中图分类号: U662.9

Review and prospect of remote control intelligent ships

知识共享许可协议
智能船舶远程驾驶控制技术研究现状与趋势王远渊,等创作,采用知识共享署名4.0国际许可协议进行许可。
  • 摘要: 阐述智能船舶及其远程驾驶的发展背景。基于目前大多数无人船艇远程控制存在的问题,在分析智能船舶远程驾驶需求和场景的基础上,提出基于人机共融理念的智能船舶远程驾驶框架。针对不同的远程驾驶模式,提出技术等级和相关的关键技术。通过借鉴交叉领域网络控制系统的发展成果,指出网络时延补偿、网络丢包补偿、安全应急、运动模型应用、运动控制、自主决策等关键技术对于实现智能船舶远程驾驶控制的重要性,阐述相关关键技术的发展现状。结合航运的运维特点,针对目前已逐步投入行业应用的船舶感知技术提出有助于实现货船远程驾驶的思考。
  • 图  1  船舶自主化等级带来的控制力变化[5]

    Figure  1.  The change of control force brought by the ship's autonomous level

    图  2  国外团队的远程驾驶实践

    Figure  2.  Remote control practice of foreign teams

    图  3  无人艇远程遥控的直接结构

    Figure  3.  Direct structure of the unmanned surface vessel's remote control

    图  4  船舶网络控制系统控制逻辑(闭环结构)

    Figure  4.  Control framework of SNCS (closed-loop structure)

    图  5  船舶网络控制系统控制逻辑(开环结构)

    Figure  5.  Control framework of SNCS (open-loop structure)

    图  6  船舶远程驾驶技术等级和实现流程

    Figure  6.  Technical level and operational process of the ship's remote control

    图  7  日本三井和古野公司合作开发的视觉和AIS信息感知增强系统[106]

    Figure  7.  Sensing awareness enhanced system proposed by MOL and Furuno using camera and AIS

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出版历程
  • 收稿日期:  2020-04-29
  • 修回日期:  2020-08-31
  • 网络出版日期:  2021-01-20
  • 刊出日期:  2021-02-28

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