无人舰艇智能航行技术进展与前沿  

Advances and frontiers of key technologies in intelligent navigation for unmanned surface vehicles

作　　者：楼建坤 徐蒙源 岳林[3] 冯伟强 王鸿东 LOU Jiankun;XU Mengyuan;YUE Lin;FENG Weiqiang;WANG Hongdong(Key Laboratory of Marine Intelligent Equipment and System,Ministry of Education,Shanghai 200240,China;State Key Laboratory of Ocean Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;China Ship Development and Design Center,Wuhan 430064,China;The 92492 Unit of PLA,Beijing 100161,China)

机构地区：[1]海洋智能装备与系统教育部重点实验室(上海交通大学),上海200240 [2]上海交通大学海洋工程全国重点实验室,上海200240 [3]中国舰船研究设计中心,湖北武汉430064 [4]中国人民解放军92942部队,北京100161

出　　处：《中国舰船研究》2025年第1期3-14,共12页Chinese Journal of Ship Research

基　　金：国家自然科学基金面上项目资助(52271348)。

摘　　要：[目的]无人舰艇智能航行系统主要负责舰艇的环境感知、决策规划和运动控制,是执行具体任务的基础。旨在梳理该系统关键技术的发展现状,剖析现存问题,并对未来发展方向提出建议,为无人舰艇智能航行关键技术的持续进步提供参考。[方法]基于近年来无人舰艇完成的百公里及千公里自主远航任务,深入综述智能航行关键技术在国内外的发展情况,通过相关技术的应用案例分析、理论研究成果梳理等方式,归纳总结当前技术的优势与不足,进而针对性地提出未来发展的关键技术方向。[结果]当前,无人舰艇智能航行技术在环境感知、决策规划和运动控制方面均取得一定进展,但仍面临诸多挑战。在环境感知方面,复杂环境下的目标感知准确性有待提升,且缺乏对波浪的实时感知能力;决策规划方面,难以有效应对动态任务场景下的多约束问题;运动控制方面,全航程多工况自适应控制能力不足。[结论]针对上述问题,建议重点发展以下关键技术:构建无人舰艇六自由度高精度运动模型,为航行决策和控制提供精准依据;利用多模态数据和人工智能前沿技术,开发感知决策大模型,增强系统的智能化水平;研究面向高海况的安全航行技术,提升无人舰艇在恶劣海洋环境中的作业能力和生存能力。[Objectives]The rapid integration of artificial intelligence(AI)into maritime technology has driven unprecedented advancements in unmanned surface vehicles(USVs),positioning them as a crucial force in future maritime operations and military transformations.The intelligent navigation system is the core of USVs,responsible for environmental perception,decision-making,and motion control,which collectively enable autonomous mission execution and integration into systematic operations.This study provides a comprehensive review of the fundamental technologies underpinning USV intelligent navigation,critically evaluates existing challenges,and proposes future research directions to advance and expand the application of intelligent navigation technologies for USVs.The research aims to bridge existing knowledge gaps,providing a foundation for the further development of autonomous maritime systems.[Method]This research provides a comprehensive review of the current state of intelligent navigation technologies for USVs,focusing on three critical areas:environmental perception,decision-making and planning,and motion control.(a)In the domain of environmental perception,the primary sensing modalities include visible light,infrared,sonar,electromagnetic signals,navigation radar,and LiDAR.With advancements in multi-source information fusion technology,perception techniques have evolved from relying on single sensors to utilizing multi-sensor fusion,transitioning from object-level fusion to feature-level fusion.Despite these advancements,achieving accurate and efficient environmental perception remains a key challenge.The ability to provide real-time,comprehensive environmental awareness is essential for USVs to navigate autonomously in complex maritime conditions.(b)For decision-making and planning,a variety of methodologies,including operations research,optimization algorithms,and AI-based approaches,have been employed to generate optimal decisions under multiple constraints,such as mission parameters,payload configurations,and

关 键 词：无人艇 环境感知 传感器数据融合 决策规划 运动控制 运动规划 大模型 

分 类 号：U664.82[交通运输工程—船舶及航道工程]