Computer Engineering and Applications ›› 2024, Vol. 60 ›› Issue (15): 1-10.DOI: 10.3778/j.issn.1002-8331.2401-0452

• Research Hotspots and Reviews • Previous Articles     Next Articles

Research on Unmanned Aerial Vehicle Swarm Resilience Assessment and Reconfiguration Technology

WEI Chenyue, HE Ming, HAN Wei, XU Xin, GAO Hong   

  1. 1.Institute of Command and Control Engineering, Army Engineering University of PLA, Nanjing 210007, China
    2.Unit 32180 of Chinese People’s Liberation Army, China
    3.College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
  • Online:2024-08-01 Published:2024-07-30

无人机集群弹性评估及重构技术研究

韦宸越,何明,韩伟,徐昕,高宏   

  1. 1.中国人民解放军陆军工程大学 指挥控制工程学院,南京 210007
    2.中国人民解放军 32180部队
    3.国防科技大学 智能科学学院,长沙 410073

Abstract: Unmanned aircraft vehicle (UAV) swarm is often affected by perturbing factors such as terrain, wind, snow, rain and fog, and anti-aircraft strikes in practical applications, which leads to the decline of swarm performance and mission accomplishment capability. In order to effectively assess and improve the swarm anti-disturbance capability, an in-depth study is carried out in terms of UAV swarm resilience assessment indexes and resilience reconfiguration methods. Firstly, the current research status of UAV swarm resilience assessment indicators is sorted out and analyzed. Secondly, the research on UAV swarm resilience reconstruction methods is summarized in terms of predictive reconstruction and anti-disturbance reconstruction. To address the problems of incomplete assessment indexes and the inability of swarm adaptive reconfiguration under multi-task and multi-disturbance situations, multi-dimensional resilience assessment indexes and UAV swarm phase change reconfiguration methods are proposed respectively, which further take into account the impact of coverage, energy consumption and other factors on swarm performance, realize the adaptive phase change of different types of tasks and disturbance types, and significantly improve the swarm’s ability to cope with disturbances. Finally, it concludes and looks forward to the future development trend of UAV swarm elastic reconfiguration.

Key words: unmanned aircraft vehicle (UAV) swarm, resilience assessment metrics, resilient reconfiguration, phase change reconfiguration

摘要: 无人机集群在实际应用中常受地形地貌、风雪雨雾、防空打击等扰动因素影响,导致集群性能下降、任务完成能力降低。为有效评估和提升集群抗扰能力,从无人机集群弹性评估指标和弹性重构方法两方面展开深入研究。梳理分析无人机集群弹性评估指标研究现状;从预测性重构和抗扰动重构两方面对无人机集群弹性重构方法进行了研究总结;针对评估指标不全面及多任务、多扰动情况下集群无法自适应重构问题,分别提出多维弹性评估指标和无人机集群相变重构方法,进一步考虑了覆盖率、能耗等因素对集群性能的影响,实现了不同任务类型和扰动种类自适应相变,大幅提升了集群应对扰动能力。最后,总结展望无人机集群弹性重构未来发展趋势。

关键词: 无人机集群, 弹性评估指标, 弹性重构, 相变重构