Review of Research Progress on AI Driven Decision and Control of Maritime Unmanned Systems

DENG Yingjie; XU Yifei; YAN Jing; ZHAO Dingxuan; LI Mengxia

doi:10.11993/j.issn.2096-3920.2025-0095

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Article Navigation > Journal of Unmanned Undersea Systems > 2026 > Accepted Manuscript

DENG Yingjie, XU Yifei, YAN Jing, ZHAO Dingxuan, LI Mengxia. Review of Research Progress on AI Driven Decision and Control of Maritime Unmanned Systems[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2025-0095

Citation:

DENG Yingjie, XU Yifei, YAN Jing, ZHAO Dingxuan, LI Mengxia. Review of Research Progress on AI Driven Decision and Control of Maritime Unmanned Systems[J]. Journal of Unmanned Undersea Systems. doi: 10.11993/j.issn.2096-3920.2025-0095

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Review of Research Progress on AI Driven Decision and Control of Maritime Unmanned Systems

doi: 10.11993/j.issn.2096-3920.2025-0095

DENG Yingjie^{1, 2
,},
XU Yifei^2
,,
YAN Jing³,
ZHAO Dingxuan^{1, 2},
LI Mengxia⁴

1.
State Key Laboratory of Crane Technology, Yanshan University, Qinhuangdao 066004, China
2.
School of Mechanical Engineering, Yanshan University, Qinhuangdao 066004, China
3.
School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
4.
State Key Laboratory of Maritime Technology and Safety, Wuhan University of Technology, Wuhan 430063, China

Received Date: 2025-07-25
Accepted Date: 2025-09-26
Rev Recd Date: 2025-09-13

Available Online: 2026-01-14

Abstract

Abstract

Maritime unmanned systems refer to intelligent unmanned platforms on the water surface, underwater, and in the air with autonomous operation capabilities. It is an inevitable development trend in the future to adopt artificial intelligence(AI) technology to improve the decision-making and control level of maritime unmanned systems. Although AI technology has made considerable progress, its application in maritime unmanned systems is still restricted by many factors such as environmental interference and system characteristics. The basic decision-making and control framework of maritime unmanned systems are illustrated at first, and the shortcomings of traditional techniques are summarized. Then, the development status of AI-driven maritime unmanned systems in various countries is expounded, and the research progress and existing problems of AI in key technologies including environmental perception and positioning, path planning and guidance, motion control, and multi-system collaboration are summarized. Finally, the challenges and development opportunities of AI supporting the decision-making and control of maritime unmanned systems are discussed.
- maritime unmanned systems,
- AI technique,
- environmental sensing and localization,
- path planning and guidance,
- motion control,
- coordination of multiple systems

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References(143)

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