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无人机集群仿生行为控制研究进展及关键技术

夏恒煜 何明 韩伟 吴晶晶 赵孝军

计算机工程与应用2026,Vol.62Issue(17):1-17,17.
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计算机工程与应用2026,Vol.62Issue(17):1-17,17.DOI:10.3778/j.issn.1002-8331.2512-0142

无人机集群仿生行为控制研究进展及关键技术

Research Progress and Key Technologies of Bionic Behavior Control for UAV Swarms

夏恒煜 1何明 2韩伟 1吴晶晶 1赵孝军1

作者信息

  • 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. 中国人民解放军陆军工程大学 指挥控制工程学院,南京 210007||近地面探测全国重点实验室,北京 100072
  • 折叠

摘要

Abstract

As the tasks and environments faced by unmanned aerial vehicle(UAV)swarms become increasingly complex,the shortcomings of traditional control methods in terms of adaptability and robustness have become more prominent.Mapping the behavioral mechanisms of biological groups to unmanned aerial vehicle(UAV)swarm systems has become an important research direction.However,existing research lacks the refinement of the behavioral mechanisms of different groups and the systematic review of related technologies.For this reason,this paper systematically reviews the current research status of bionic behavior control for UAVs,with a focus on three typical objects:bee colonies,wolf packs,and bird flocks.Firstly,the paper expounds the internal structure,interaction methods and behavioral mechanisms of three typical bionic groups.Secondly,it analyzes the key technologies of bionic behavior control for UAVs and summarizes the advantages and disadvantages of each method as well as their applicable scenarios.To address the challenges of adapt-ability and flexibility in bionic behavior control for unmanned aerial vehicle swarms,a bionic behavior control strategy based on behavior cloning is proposed.Finally,the paper summarizes and looks forward to the future development trends of the research on bionic behavior control methods for unmanned aerial vehicle swarms.

关键词

无人机集群/群体行为/仿生行为控制/行为克隆

Key words

unmanned aerial vehicle(UAV)swarm/group behavior/bionic behavior control/behavioral cloning

分类

信息技术与安全科学

引用本文复制引用

夏恒煜,何明,韩伟,吴晶晶,赵孝军..无人机集群仿生行为控制研究进展及关键技术[J].计算机工程与应用,2026,62(17):1-17,17.

基金项目

国家自然科学基金(62273356) (62273356)

国家级人才项目(2022-JCJQ-ZQ-001) (2022-JCJQ-ZQ-001)

国家重点研发计划(2024YFF140140) (2024YFF140140)

启元国家实验室创新基金(2025-JCJQ-LA-001-101) (2025-JCJQ-LA-001-101)

江苏省重点研发计划(BE2023809). (BE2023809)

计算机工程与应用

1002-8331

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