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1. 西北工业大学 电子信息学院, 陕西 西安 710072
2. 国防科技大学 智能科学学院, 湖南 长沙 410073
3. 西北工业大学 航空学院, 陕西 西安 710072
Received:05 September 2024,
Published Online:12 August 2025,
Published:31 July 2025
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Jun CHEN, Yan TONG, Yifeng NIU, et al. A Review on Fuzzy Cognitive Map and Its Applications in Unmanned Systems[J]. Acta Armamentarii, 2025, 46(7): 240804.
Jun CHEN, Yan TONG, Yifeng NIU, et al. A Review on Fuzzy Cognitive Map and Its Applications in Unmanned Systems[J]. Acta Armamentarii, 2025, 46(7): 240804. DOI: 10.12382/bgxb.2024.0804.
模糊认知图作为一种兼具模糊推理和类神经网络特征的知识图解软计算模型
与第3代人工智能知识与数据双驱动的发展方向高度契合
已被广泛应用于各个领域。首先
介绍模糊认知图理论的基本概念和原理
从构建方法、学习算法、拓展模型3个方面系统地分析模糊认知图的最新研究进展和存在的主要问题
总结未来研究的主要方向和重点内容;其次
全面梳理和归纳模糊认知图在无人系统(单无人系统、多无人系统、无人-有人系统)中的应用研究情况;最后
通过详细分析自主智能驱动的单无人系统、群体智能驱动的多无人系统以及互信智能驱动的无人-有人系统的技术需求
深入讨论未来模糊认知图在无人系统应用中的重点研究内容和主要研究思路。
Fuzzy cognitive map (FCM)
as a kind of knowledge graphical soft computing model with both fuzzy reasoning and neural network-like features
is highly compatible with the development direction of the third generation of artificial intelligence driven by both knowledge and data
and has been widely used in various fields.Firstly
the basic concepts and principles of FCM theory are introduced
the latest research progress and major existing problems of FCM are systematically analyzed from the three aspects of construction method
learning algorithm and extension model
and the main directions and key contents of the future research are summarized.Secondly
the application research of FCM in unmanned systems (single unmanned systems
multi-unmanned systems
unmanned-manned systems) are comprehensively reviewed and summarized.Finally
the key research contents and main research ideas of FCM in unmanned systems applications in the future are discussed in depth by analyzing in detail the technical requirements of single unmanned systems driven by autonomous intelligence
multi-unmanned systems driven by swarm intelligence
and unmanned-manned systems driven by mutual trust intelligence.
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LI Y J , HUANG Q L , YANG L , et al. Combat intention recognition of air cluster targets driven by data and knowledge [J ] . Acta Armamentarii , 2025 , 46 ( 2 ): 240113 . (in Chinese) DOI: 10.12382/bgxb.2024.0113 http://doi.org/10.12382/bgxb.2024.0113 Aiming at the diverse spatiotemporal characteristics of cluster targets and the excessive reliance of traditional data driven models on empirical samples,this paper proposes an algorithm for combat intent recognition driven by both data and knowledge.A cluster feature vector based on the virtual envelope and minimum bounding rectangle of target formation are constructed to enhance the feature expression of enemy situation data,which takes the cluster characteristics,such as the spatial form of cluster targets,into account.A knowledge model based on military expert experience and a long short-term memory (LSTM) network model with attention mechanism are established then.The knowledge model generates the intent pre-recognition vectors based on constraint rule,while the LSTM network model predicts the residual of intent probability distribution.The fusion ratio of both models is adaptively adjusted by utilizing a learnable residual estimator structure.A multi-objective loss function is designed to control the influence weights of the dual models.Ultimately,the fusion of the dual models overcomes the contradiction between the high accuracy of traditional data models and the insufficient data samples.Experimental results indicate that the proposed method improves the recognition accuracy to about 5.34% and 4.98% compared to LSTM and Attention-LSTM,respectively,and has significantly lower dependence on sample size than traditional data-driven methods.
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薛建儒 , 房建武 , 吴俊 , 等 . 多机协同智能发展战略研究 [J ] . 中国工程科学 , 2024 , 26 ( 1 ): 101 - 116 . DOI: 10.15302/J-SSCAE-2024.01.013 http://doi.org/10.15302/J-SSCAE-2024.01.013 多个自主智能系统通过信息、行为交互构成的多机协同智能,代表着未来智能系统的必然发展趋势,是我国新一代人工智能规划部署的主攻方向,也是支撑国防、社会安全的核心技术和推动制造业由大到强的必由之路。开展突破多机协同智能技术发展研究,对于推动我国军事智能、智能产业高质量发展、加快工业转型升级具有重要意义。本文基于多机协同智能系统当前面临的难以适应复杂任务这一挑战,从基础理论和核心关键技术两个层面出发,系统地梳理了多机协同智能的研究现状,分析了制约基础理论与关键技术发展的主要瓶颈性问题,并以多机协同智能制造为典型应用,剖析理论与技术发展中存在的问题。研究认为,多机协同智能将朝着人机群组智能的方向发展,为抢占发展先机,需及早布局人机群组智能的基础理论探索,加速核心技术突破,并加快应用示范。
XUE J R , FANG J W , WU J , et al. Collaborative multiple autonomous systems [J ] . Strategic Study of CAE , 2024 , 26 ( 1 ): 101 - 116 . (in Chinese) DOI: 10.15302/J-SSCAE-2024.01.013 http://doi.org/10.15302/J-SSCAE-2024.01.013 Collaborative intelligence formed via information and behavioral interactions of multiple autonomous systems is an inevitable trend of future intelligent systems. It is a focus of planning of the next-generation artificial intelligence in China and is crucial for supporting national security and strengthening the manufacturing industry. Research aimed at overcoming bottlenecks regarding collaborative multiple autonomous systems will significantly aid the advancement of intelligent industries and accelerate industrial transformation and upgrading in China. Focusing on the challenge that collaborative multiple autonomous systems cannot adapt to complex tasks, this study thoroughly analyzes the research status and major bottlenecks of collaborative multiple autonomous systems from the aspects of fundamental research and engineering. Using multi-robot collaborative intelligent manufacturing as an example, we provide an in-depth analysis of relevant theoretic and technical problems. Our research indicates that collaborative multiple autonomous systems will inevitably evolve toward human ‒ machine teaming. To master this opportunity, it is critical to proactively lay the groundwork for the theoretical exploration and technological breakthroughs of human‒machine teaming and to conduct exemplary applications.
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SU B , JIANG L , LIU Y F , et al. A review of key technologies for cross-domain and trans-medium of mobile robotics [J ] . Acta Armamentarii , 2023 , 44 ( 9 ): 2556 - 2567 . (in Chinese) DOI: 10.12382/bgxb.2023.0414 http://doi.org/10.12382/bgxb.2023.0414 Human exploration of terrestrial, aerial, spatial, and aquatic environments has never ceased, and this process involves complex scientific problems related to multi-domain and multi-medium environments.As typical examples of machines capable of crossing different environments, mobile robots are expected to explore broader land, higher sky, farther space, and deeper seabed in the future but this presents a significant challenge for mobile robots to maintain high performance in multi-domain and multi-medium environments.This paper first introduces the scientific fusion of mobile robots in energy, space-time, and information domains, highlighting their increasingly important role in exploring new domains and media.Then, it summarizes the basic theoretical research, applications, and development status of mobile robots in areas such as supporting and traction technology, speed and stability technology, and interaction and collaborative technology.Finally, suggestions are proposed to address the key challenges related to the maneuverability and operational intelligence of multi-domain and multi-medium mobile robots.The aim is to enable these machines to perform tasks that are beyond human reach, and to facilitate the widespread application of robot equipment systems in multi-domain and multi-medium environments.
陈军 , 徐嘉 , 高晓光 . 基于ABFCM模型框架的UCAV自主攻击决策 [J ] . 系统工程与电子技术 , 2017 , 39 ( 3 ): 549 - 556 .
CHEN J , XU J , GAO X G . Autonomous attack decision-making of UCAV based on ABFCM model framework [J ] . Systems Engineering and Electronics , 2017 , 39 ( 3 ): 549 - 556 . (in Chinese) DOI: 10.3969/j.issn.1001-506X.2017.03.14 http://doi.org/10.3969/j.issn.1001-506X.2017.03.14 <p>In order to exert the autonomy of unmanned combat aerial vehicle&rsquo;s(UCAV) decision-making and relieve the operator&rsquo;s task burden, based on the agentbased fuzzy cognitive map(ABFCM) model framework, the three-level UCAV&rsquo;s autonomous attack decision-making model is designed, which contains information processing, decision reasoning and human-vehicle interaction. The contents of UCAV&rsquo;s autonomous attack decision-making are decomposed into agents of different levels and effects. On the basis of respectively constructing the causal inference model of every agent, the whole decision inference behavior is organized legitimately and orderly. Simulation analysis proves the model&rsquo;s rationality and feasibility, simultaneously it demonstrates that the autonomous attack decisionmaking model will help UCAV adapt to the increasingly complex battle-field environment, and enhance the independent combat capability under the supervisory control mode.</p>
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LI J , CHEN S C . Overview of key technology and its development of drone swarm [J ] . Acta Armamentarii , 2023 , 44 ( 9 ): 2533 - 2545 . (in Chinese) DOI: 10.12382/bgxb.2023.0514 http://doi.org/10.12382/bgxb.2023.0514 Modern warfare modes have given birth to the drone swarms as a new type of operational pattern. The concept of forming the advanced group intelligent behavior obtained by using drones with simple functions, which applies the natural bee swarm organization algorithm,is systematically analyzed. The classification and characteristics of drone swarm are introduced. The key technologies and development status of collaborative networking, sensing, decision-making and control are summarized. Focusing on the practical requirements under complex countermeasure environments, the key points and difficulties in the development of unmanned drone swarm technology which integrates electro-optic detection, communication networking, collaborative control and task planning into one are presented. The development approaches and measures of the drone swarm technologies are also put forward, hoping to achieve the goal of leading the development direction of unmanned drone swarm technology and promoting the corresponding technologies to practical applications.
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陈军 , 梁晶 , 程龙 , 等 . 基于FCM的多无人机协同攻击决策建模方法 [J ] . 航空学报 , 2022 , 43 ( 7 ): 325526 . DOI: 10.7527/S1000-6893.2021.25526 http://doi.org/10.7527/S1000-6893.2021.25526 针对复杂不确定战场环境下多无人机协同任务的需求,提出了一种基于模糊认知图(FCM)及其扩展模型的多无人机协同攻击决策建模方法。基于人的决策心智模式,采用智能体模糊认知图(ABFCM)建立了包含感性和理性2种决策模式的多无人机协同攻击决策系统模型框架。采用模糊灰色认知图(FGCM)对多无人机的态势感知和协同攻击决策开展了建模工作。借鉴人脑杏仁核机理建立了态势-决策模板快速匹配的感性攻击决策模型。为降低建模工作对专家知识的依赖,采用直觉模糊集的决策阈值算法提高理性攻击决策模型的客观性,并采用动量梯度下降(MGD)学习算法进一步提高了决策模型的学习进化能力。通过仿真验证分析表明,基于FCM的多无人机协同攻击决策建模方法能够较好地应对复杂不确定战场环境,发挥知识和数据在建模中的综合作用,可为提升多无人机执行任务的决策优势提供理论指导和建模方法参考。
CHEN J , LIANG J , CHENG L , et al. Cooperative attack decision modeling method of multiple UAVs based on FCM [J ] . Acta Aeronautica et Astronautica Sinica , 2022 , 43 ( 7 ): 325526 . (in Chinese) DOI: 10.7527/S1000-6893.2021.25526 http://doi.org/10.7527/S1000-6893.2021.25526 According to the requirements for multi-UAV cooperative mission in the complex and uncertain battlefield environment, a decision-making modeling method of multi-UAV cooperative attack based on the Fuzzy Cognitive Map (FCM) and its extended model are proposed. Based on the human decision-making mental model, the model framework of the multi-UAV cooperative attack decision-making system including the perceptual and rational decision-making modes is established by using the Agent-Based Fuzzy Cognitive Map (ABFCM). The Fuzzy Grey Cognitive Map (FGCM) is used to model the situation awareness and cooperative attack decision of multi-UAVs. Based on the amygdala mechanism of human brain, a perceptual attack decision model for quick matching of situation and decision template is established. To reduce the dependence of modeling work on expert knowledge, a rational attack decision model is established based on the decision threshold algorithm of intuitionistic fuzzy sets, and the learning and evolution ability of the decision model is further improved by using the Momentum Gradient Descent (MGD) learning algorithm. The simulation results show that the method proposed can better cope with the complex and uncertain battlefield environment, give full play to the comprehensive role of knowledge and data in modeling, and provide theoretical and modeling guidance for improving the decision-making advantages in mission execution by multi-UAVs.
陈军 , 张岳 , 陈晓威 , 等 . 基于模糊灰色认知图的复杂战场智能态势感知建模方法 [J ] . 兵工学报 , 2022 , 43 ( 5 ): 1093 - 1106 . DOI: 10.12382/bgxb.2021.0259 http://doi.org/10.12382/bgxb.2021.0259 针对复杂战场环境的动态、不确定性特征,提出一种基于模糊灰色认知图(FGCM)的智能态势感知(SA)建模方法。基于SA理论,采用自上而下任务驱动的态势觉察方式实现态势元素的提取;以目标威胁评估为态势理解的建模对象,利用FGCM在不确定数据表达和推理的模型特性,同时引入外部环境控制节点建立威胁评估动态FGCM模型。以目标意图预测为态势预测的建模对象,在基于专家知识建立的FGCM模型结构基础上,采用粒子群优化算法提高了意图预测模型对历史数据样本的参数学习能力。仿真验证分析结果表明,基于FGCM的智能SA建模方法能够较好地应对动态、不确定的战场环境,发挥知识和数据在建模中的综合作用。
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王童豪 , 彭星光 , 胡浩 , 等 . 海上有人/无人协同系统及其关键技术综述 [J ] . 兵工学报 , 2024 , 45 ( 10 ): 3317 - 3340 . DOI: 10.12382/bgxb.2024.0327 http://doi.org/10.12382/bgxb.2024.0327 海上有人/无人协同系统对进一步提升海军作战效能有重要作用,是现代海军装备发展的重要方向。立足未来海上作战,以海上有人/无人协同系统的实际应用为牵引,综述国外相关项目发展现状,厘清海上有人/无人协同系统的主要特点,凝练并分析其中科学问题与关键技术,总结海上有人/无人协同系统的发展方向、矛盾与挑战。未来,智能化、模块化和稀疏化将成为海上有人/无人协同系统的重要发展方向,但由于系统自主性与可控性间、智能化发展与海上约束间、海上有人/无人协同特点与现有协同任务体系间存在一定的发展矛盾,故系统还将面临系统规模、平台多样性、系统安全性及信息化与智能化等方面的发展挑战。
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陈军 , 张新伟 , 徐嘉 , 等 . 有人/无人机混合编队有限干预式协同决策 [J ] . 航空学报 , 2015 , 36 ( 11 ): 3652 - 3665 . DOI: 10.7527/S1000-6893.2015.0085 http://doi.org/10.7527/S1000-6893.2015.0085 针对Leader-Follower异构型有人/无人机混合编队协同决策系统具有递阶分布式决策结构、决策信息分散以及通信约束等特点,在智能体模糊认知图(ABFCM)和动态模糊认知图(DFCM)的理论基础上,提出了一种有限干预式协同决策机制。通过构建层次化的Follower平台自主决策模型,实现了该平台与外部系统良好的交互能力,体现了自主决策的"动态性"。通过设计Leader平台的3种干预策略,满足了不同层次的决策需求,体现了干预过程的"有限性"。仿真结果表明:有限干预协同决策模型能够适应外部环境的动态变化,充分发挥Follower平台的自主决策能力;而不同层次的有限干预介入既减轻了Leader平台的控制负荷,又保证了决策的有效性和可行性,可为解决其他同类复杂系统的协同决策问题提供理论依据和方法参考。
CHEN J , ZHANG X W , XU J , et al. Human/unmanned-aerial-vehicle team collaborative decision-making with limited intervention [J ] . Acta Aeronautica et Astronautica Sinica , 2015 , 36 ( 11 ): 3652 - 3665 . (in Chinese) DOI: 10.7527/S1000-6893.2015.0085 http://doi.org/10.7527/S1000-6893.2015.0085 In view of the characteristics of Leader-Follower heterogeneous multi-platform system for the human/unmanned aerial vehicle team which are hierarchical and distributed structure, decision-making information decentralization and communication constraints, the collaborative decision-making mechanism with limited intervention based on the combination of agent-based fuzzy cognitive map (ABFCM) and dynamic fuzzy cognitive map (DFCM) is presented. In the proposed approach, hierarchical autonomous decision-making model for Follower platform is developed in order to make the Follower able to interact with external environment well and reflect the autonomous decision-making dynamics. Three intervention strategies under different conditions are designed for Leader platform to meet the requirements of different decision levels. Meanwhile these strategies reflect the limitation of intervention processes. Simulation results show that intervention-limited collaborative decision-making mechanism can adapt to dynamic changes in the external environment and make full use of Follower platform's autonomous decision-making ability. Hierarchical limited interventions can reduce the control workload of Leader and ensure the effectiveness and feasibility of decision-making as well. This work also provides a theoretical basis and methodology support to solve other similar collaborative decision-making problem in complex systems.
CHEN J , QIU X J , RONG J , et al. Design method of organizational structure for MAVs and UAVs heterogeneous team with adjustable autonomy [J ] . Journal of Systems Engineering and Electronics , 2018 , 29 ( 2 ): 286 - 295 . DOI: 10.21629/JSEE.2018.02.09 http://doi.org/10.21629/JSEE.2018.02.09 The increasingly complex battlefield environment requests much closer connection in a team having both manned and unmanned aerial vehicles (MAVs and UAVs). This special heterogeneous team structure causes demands for effective organizational structure design solutions. Implementing adjustable autonomy in the organizational structure, the expected evaluation function is established based on the physical resource, intelligent resource, network efficiency, network vulnerability and task execution reliability. According to the above constraints, together with interaction latency, decision-making information processing capacity, and decision-making latency, we aim to find a preferential organizational structure. The proposed organizational structure includes cooperative relationships, supervisory control relationships, and decision-making authorization relationships. In addition, by considering the influence on the intelligent support capabilities and the task execution reliability created by adjustable autonomy, it helps to build the proposed organizational structure designed with certain degree of flexibility to deal with the potential changes in the unpredictable battlefield environment. Simulation is conducted to confirm our design to be valid. And the method is still valid under different battlefield environments and interventions.
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钟赟 , 姚佩阳 , 张杰勇 , 等 . 基于HFCM的有人-无人机作战系统交互式协同决策 [J ] . 系统工程理论与实践 , 2021 , 41 ( 10 ): 2748 - 2760 . DOI: 10.12011/SETP2020-0283 http://doi.org/10.12011/SETP2020-0283 针对有人-无人机作战系统中的交互式协同决策问题,本文基于模糊认知图(fuzzy cognitive map,FCM)理论,提出一种基于混合模糊认知图(hybrid fuzzy cognitive map,HFCM)的决策方法.首先,分析现有有人-无人机交互式协同决策模式研究的不足,在相关研究理论基础上,建立交互式协同决策框架,包括无人机自主决策和有人机干预决策(环境干预、知识干预和推理干预).然后,结合基于规则的模糊认知图(rule-based fuzzy cognitive map,RBFCM)和直觉模糊认知图(intuitionistic fuzzy cognitive map,IFCM),建立交互式协同决策HFCM模型:在武器系统检测阶段,基于RBFCM推理得到武器发射条件;在攻击态势评估阶段,基于IFCM进行动态推理得到环境干预结果,并设计相应的知识和推理干预策略.最后,通过一组典型案例,验证了本文方法的有效性.
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向锦武 , 董希旺 , 丁文锐 , 等 . 复杂环境下无人集群系统自主协同关键技术 [J ] . 航空学报 , 2022 , 43 ( 10 ): 527570 . DOI: 10.7527/S1000-6893.2022.27570 http://doi.org/10.7527/S1000-6893.2022.27570 在高动态、不确定、资源受限等复杂环境下,无人集群系统执行协同区域搜索、集群优化调度等任务将会面临"感知—判断—决策—行动(OODA)"回路各个领域的挑战。为了提升无人集群系统的任务场景适应能力,必须突破复杂环境下无人集群系统自主协同关键技术。以复杂环境下大规模异构无人集群鲁棒自主协同理论为基础,探讨了复杂环境下无人集群系统自适应异构体系架构设计与建模方法,梳理了复杂环境下高维态势分布式感知与认知、可引导、可信任、可进化的智能决策、复杂环境下无人集群系统自主协同控制3个科学问题。首先综述了复杂环境下无人集群系统自主协同的研究进展;其次,分析了无人集群系统OODA任务回路面临的挑战;然后,初步梳理了复杂环境下无人集群系统自主协同涉及的各项关键技术及其进展;最后,给出了无人集群系统自主协同领域未来发展的思考。
XIANG J W , DONG X W , DING W R , et al. Key technologies for autonomous cooperation of unmanned swarm systems in complex environments [J ] . Acta Aeronautica et Astronautica Sinica , 2022 , 43 ( 10 ): 527570 . (in Chinese) DOI: 10.7527/S1000-6893.2022.27570 http://doi.org/10.7527/S1000-6893.2022.27570 In complex environments with high dynamics, uncertainty and resource constraints, the unmanned swarm system will face challenges in all fields of the "Observation-Orientation-Decision-Action (OODA)" loop when performing complicated tasks such as collaborative area search and swarm optimal scheduling. To improve the adaptability of unmanned swarm systems to different scenarios, it is necessary to break through the key technologies for autonomous cooperation of unmanned swarm systems in complex environments. Based on the theory of robust autonomous cooperation of large-scale heterogeneous unmanned swarm systems in complex environments, this paper gives a review of the design and modeling methods of adaptive heterogeneous architecture for unmanned swarm systems, and discusses three problems:high-dimensional situation distributed perception and cognition, intelligent decision-making with guiding, trusting and evolving ability, and autonomous cooperative control of the unmanned swarm system in complex environments. Firstly, the research progress of autonomous cooperation of unmanned swarm system in complex environment is summarized. Secondly, the challenges faced by OODA task loop of unmanned swarm system are analyzed. Then, the key technologies involved in autonomous cooperation of unmanned swarm system in complex environment and their progress are reviewed. Finally, the future development of autonomous cooperation of unmanned swarm system is given.
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