无人艇作为未来海战场的主要作战力量,适宜在恶劣海况下执行长时高风险任务,其自主决策能力是无人艇执行作战任务的核心能力,能够显著提升无人艇的智能程度,是获取作战优势的关键要素。在对无人艇自主决策特点研究的基础上,提出无人艇自主决策架构。通过分析决策框架中认知技术、筹划技术、临机决策技术、数字孪生技术等方面的发展现状,提出海战场抽象建模困难、对抗性强、无人作战规则不完善、人工智能可用度不高等挑战问题,指出高适应性的自主决策技术、基于数字孪生的平行决策技术等研究方向。
As the main combat force in the future sea battlefield, unmanned surface vehicles are suitable for carrying out long-term high-risk tasks in harsh sea conditions. Their autonomous decision-making ability is the core ability of unmanned surface vehicles to carry out combat tasks, which can significantly improve their intelligence and is a key element in obtaining combat advantages. On the basis of studying the characteristics of autonomous decision-making for unmanned surface vehicles, a framework for autonomous decision-making for unmanned surface vehicles is proposed. By analyzing the current development status of cognitive technology, planning technology, ad-hoc decision-making technology, and digital twin technology in decision-making frameworks, challenges such as difficulty in abstract modeling, strong adversarial nature, imperfect unmanned combat rules, and low availability of artificial intelligence in naval battlefields were proposed. Research directions such as highly adaptable autonomous decision-making technology and parallel decision-making technology based on digital twins were pointed out.
2025,47(5): 8-15 收稿日期:2024-3-12
DOI:10.3404/j.issn.1672-7649.2025.05.002
分类号:U661.43;E919
基金项目:国防预研项目(JCKY2021206B015)
作者简介:蔡庆(1975 – ),男,硕士,研究员,研究方向为水面无人系统
参考文献:
[1] 冯炜, 崔东华, 夏天冰, 等. 国外无人船集群运用特点分析及其应对启示[J]. 中国舰船研究, 2023, 18(1): 1-12.
FENG W, CUI D H, XIA T B, et al. Analysis of characteristics of foreign unmanned surface vehicle swarm combat application and proposed countermeasures[J]. Chinese Journal of Ship Research, 2023, 18(1): 1-12.
[2] 谢少荣, 刘坚坚, 张丹. 复杂海况无人艇集群控制技术研究现状与发展[J]. 水下无人系统学报, 2020, 28(6): 584-596.
XIE S R, LIU J J, ZHANG D. Current development of control technology for unmanned surface vessel clusters under complex sea conditions[J]. Journal of Unmanned Undersea Systems, 2020, 28(6): 584-596.
[3] 申家双, 王耿峰, 陈长林. 海洋环境装备体系建设现状及发展策略[J]. 海洋测绘, 2017, 37(4): 33-38.
SHEN J S, WANG G F, CHEN C L. The constructional status and strategies on the equipmental systems of marine environment[J]. Hydrographic Surveying and Charting, 2017, 37(4): 33-38.
[4] 袁翔, 左毅, 王菁, 等. 数据驱动的态势认知技术及发展思考[J]. 中国电子科学研究院学报, 2022, 17(2): 134-140.
YUAN X, ZUO Y, WANG J, et al. Data-driven situation cognition technology and development idea[J]. Journal of CAEIT, 2022, 17(2): 134-140.
[5] 王玉竹, 闫浩文. 一种改进的群组目标空间方向关系计算模型[J]. 测绘科学, 2022, 47(4): 169-174.
WANG Y Z, YAY H W. An improved computational model on spatial direction between object groups[J]. Science of Surveying and Mapping, 2022, 47(4): 169-174.
[6] 冷画屏, 关庆云, 吴晓锋. 基于领域知识的海上编队线型队形识别[J]. 舰船科学技术, 2013, 35(2): 103-106.
LENG H P, GUAN Q Y, WU X F. Recognition of naval fleet line type formation based on domain knowledge[J]. Ship Science and Technology, 2013, 35(2): 103-106.
[7] 梁吉业, 冯晨娇, 宋鹏. 大数据相关分析综述[J]. 计算机学报, 2016, 39(1): 1-18.
LIANG J Y, FENG C J, SONG P. A survey on correlation analysis of big data[J]. Chinese Journal of Computers, 2016, 39(1): 1-18.
[8] SZÉKELY G J, RIZZO M L, BAKIROV N K. Measuring and testing dependence by correlation of distances[J]. The Annals of Statistics, 2007, 35(6). 2769-2794.
[9] MARTÍNEZ-GÓMEZ E, RICHARDS M T, RICHARDS D St P. Distance correlation methods for discovering associations in large astrophysical databases[J]. The Astrophysical Journal, 2014, 781(1): 39.
[10] EDELMANN D, FOKIANOS K, PITSILLOU M. An updated literature review of distance correlation and its applications to time series[J]. International Statistical Review, 2019, 87(2): 237-262.
[11] 伍之前, 李登峰. 基于推理和多属性决策的空中目标攻击意图判断模型[J]. 电光与控制, 2010, 17(5): 10-13.
WU Z Q, LI D F. A model for aerial target attacking intention judgment based on reasoning and multi-attribute decision making[J]. Electronics Optics & Control, 2010, 17(5): 10-13.
[12] 乔殿峰, 梁彦, 马超雄, 等. 多域作战下的群目标意图识别与预测[J]. 系统工程与电子技术, 2022, 44(11): 3403-3412.
QIAO D F, LIANG Y, MA C X, et al. Recognition and prediction of group target intention in multi-domain operation[J]. Systems Engineering and Electronics, 2022, 44(11): 3403-3412.
[13] 李战武, 李双庆, 彭明毓, 等. 基于注意力机制改进的LSTM空战目标意图识别方法[J]. 电光与控制, 2023, 30(3): 1-7.
LI Z W, LI S Q, PENG M Y, et al. Air combat intention recognition method of target based on LSTM improved by attention mechanism[J]. Electronics Optics & Control, 2023, 30(3): 1-7.
[14] RAHMES M, WILDER K, FOX K, et al. A game theory model for situation awareness and management[C]//2013 IEEE 10th Consumer Communications and Networking Conference (CCNC). Las Vegas, NV: IEEE, 2013: 909-913[2023-12-05].
[15] GUO L, YAN F, LI T, et al. An automatic method for constructing machining process knowledge base from knowledge graph[J]. Robotics and Computer-Integrated Manufacturing, 2022, 73: 102222.
[16] DU C, WANG J, SUN H, et al. Syntax-type-aware graph convolutional networks for natural language understanding[J/OL]. Applied Soft Computing, 2021, 102: 107080.
[17] HATANAKA W, YAMASHINA R, MATSUBARA T. Reinforcement learning of action and query policies with LTL instructions under uncertain event detector[J]. IEEE Robotics and Automation Letters, 2023, 8(11): 7010-7017.
[18] 曾宏, 张伟斌, 张云飞, 等. 小型无人艇编队的多任务协同控制方法[J]. 舰船科学技术, 2022, 44(9): 69-74.
ZENG H, ZHANG W B, ZHAO J C, et al. Research on multi-task cooperative control method for small unmanned boat formation[J]. Ship Science and Technology, 2022, 44(9): 69-74.
[19] 翟政, 何明, 徐鹏, 等. 基于市场机制的无人集群任务分配研究综述[J]. 计算机应用研究, 2023, 40(7): 1921-1928.
ZHAI Z, HE M, XU P, et al. Research review of task allocation for unmanned swarm based on market mechanism[J]. Application Research of Computers, 2023, 40(7): 1921-1928.
[20] 杨旭, 王锐, 张涛. 面向无人机集群路径规划的智能优化算法综述[J]. 控制理论与应用, 2020, 37(11): 2291-2302.
YANG X, WANG R, ZHANG T. Review of unmanned aerial vehicle swarm path planning based on intelligent optimization[J]. Control Theory & Applications, 2020, 37(11): 2291-2302.
[21] 房肖, 温广辉, 付俊杰, 等. 基于博弈的水面无人艇集群对抗问题研究[J]. 控制工程, 2022, 29(3): 492-497.
FANG X, WEN G H, FU J J, et al. Study on group confrontation of unmanned surface vessels based on game theory[J]. Control Engineering of China, 2022, 29(3): 492-497.
[22] 刘杰, 薛占熬. 不完备信息系统的梯形模糊数三支决策模型[J]. 山西大学学报(自然科学版), 2017, 40(4): 683-689.
LIU J, XUE Z. Trapezoidal fuzzy number three-way decision model for incomplete information systems[J]. Journal of Shanxi University (Nat. Sci. Ed. ), 2017, 40(4): 683-689.
[23] 苏震, 张钊, 陈聪, 等. 基于深度强化学习的无人艇集群博弈对抗[J]. 兵器装备工程学报, 2022, 43(9): 9-14.
SU Z, ZHANG Z, CHEN C, et al. Deep reinforcement learning based swarm game confrontation of unmanned surface vehicles[J]. Journal of Ordnance Equipment Engineering, 2022, 43(9): 9-14.
[24] 王鹏, 杨妹, 祝建成, 等. 面向数字孪生的动态数据驱动建模与仿真方法[J]. 系统工程与电子技术, 2020, 42(12): 2779-2786.
WANG P, YANG M, ZHU J C, et al. Dynamic data driven modeling and simulation method for digital twin[J]. Systems Engineering and Electronics, 2020, 42(12): 2779-2786.