复杂环境下无人集群系统自主协同关键技术

doi:10.7527/S1000-6893.2022.27570

电子电气工程与控制

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复杂环境下无人集群系统自主协同关键技术

向锦武^1,2,3, 董希旺^2,4, 丁文锐³, 索津莉⁵, 沈林成⁶, 夏辉⁷

1. 北京航空航天大学航空科学与工程学院, 北京 100191;
2. 北京航空航天大学人工智能研究院, 北京 100191;
3. 北京航空航天大学无人系统研究院, 北京 100191;
4. 北京航空航天大学自动化科学与电气工程学院, 北京 100191;
5. 清华大学自动化系, 北京 100084;
6. 国防科技大学研究生院, 长沙 410073;
7. 北京电子工程总体研究所, 北京 100074

收稿日期:2022-06-04 修回日期:2022-06-17 发布日期:2022-07-14
通讯作者: 董希旺,E-mail:xwdong@buaa.edu.cn E-mail:xwdong@buaa.edu.cn
基金资助:
2020年度科技创新2030-"新一代人工智能"重大项目（2020AAA0108200）

Key technologies for autonomous cooperation of unmanned swarm systems in complex environments

XIANG Jinwu^1,2,3, DONG Xiwang^2,4, DING Wenrui³, SUO Jinli⁵, SHEN Lincheng⁶, XIA Hui⁷

1. School of Aeronautical Science and Engineering, Beihang University, Beijing 100191, China;
2. Institute of Artificial Intelligence, Beihang University, Beijing 100191, China;
3. Institute of Unmanned System, Beihang University, Beijing 100191, China;
4. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China;
5. Department of Automation, Tsinghua University, Beijing 100084, China;
6. Graduate School, National University of Defense Technology, Changsha 410073, China;
7. Beijing Institute of Electronic System Engineering, Beijing 100074, China

Received:2022-06-04 Revised:2022-06-17 Published:2022-07-14
Supported by:
Science and Technology Innovation 2030-Key Project of "New Generation Artificial Intelligence" (2020AAA0108200)

摘要/Abstract

摘要： 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。

关键词: 无人集群系统, 异构体系架构, 分布式感知与认知, 智能决策与规划, 协同控制, 仿真应用验证

Abstract: 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.

Key words: unmanned swarm system, heterogeneous system architecture, distributed perception and cognition, intelligent decision making and planning, cooperative control, simulation and application validation

中图分类号:

V279

向锦武, 董希旺, 丁文锐, 索津莉, 沈林成, 夏辉. 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): 527570-527570.

XIANG Jinwu, DONG Xiwang, DING Wenrui, SUO Jinli, SHEN Lincheng, XIA Hui. Key technologies for autonomous cooperation of unmanned swarm systems in complex environments[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(10): 527570-527570.

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