无人机集群智能的生成样式研究

doi:10.3969/j.issn.1009-086x.2020.05.007

现代防御技术 ›› 2020, Vol. 48 ›› Issue (5): 44-49.DOI: 10.3969/j.issn.1009-086x.2020.05.007

无人机集群智能的生成样式研究

许瑞明

军事科学院评估论证研究中心,北京 100091

收稿日期:2020-03-17 修回日期:2020-03-31 出版日期:2020-10-20 发布日期:2021-02-01
作者简介:许瑞明(1963-),男,江苏南通人。研究员,硕士,主要从事军事运筹、作战建模与仿真研究。通信地址:100091 北京市海淀区厢红旗东门外1号评估论证研究中心 E-mail:2557263279@qq.com

Research on Generation Style of UAV Cluster Intelligence

XU Rui-ming

Center of Assessment and Demonstration Research,Academy of Military Science,Beijing 100091,China

Received:2020-03-17 Revised:2020-03-31 Online:2020-10-20 Published:2021-02-01

摘要/Abstract

摘要： 无人机集群作战是未来的重要作战方式。无人机集群智能的生成模式及其应用实现途径等智能生成样式问题研究是无人机集群作战编成确定和作战运用设计的基础支撑。归纳提出了无人机集群智能的集中式、仿生行为式和功能分布式生成模式,并从总体上探讨了相应的应用实现途径;提出了基于平行系统架构的战中任务调整和航路再规划智能效果实现途径;研究提出了仿生行为智能涌现运用于陌生环境下航路搜索、攻击与优化的方法途径。

关键词: 无人机, 集群智能, 生成样式, 实现途径, 平行系统, 仿生智能

Abstract: Unmanned aerial vehicle (UAV) cluster operation is an important operation mode in the future.The research on the generation mode of UAV cluster intelligence and the way to realize it is the basic support for the determination of UAV cluster operational organization and operational design.Firstly,the centralized,bionic and function distributed generation model of UAV cluster intelligence is proposed,and the corresponding ways of realization are discussed in general.Secondly,the way to realize intelligent effect of task adjustment and route replanning in war is proposed, based on parallel system architecture.Finally,the way of route search,attack and optimization based on emergence of bionic behavior intelligence is proposed.

Key words: unmanned aerial vehicle (UAV), intelligence of cluster, generation style, realization way, parallel system, bionic intelligence

中图分类号:

许瑞明. 无人机集群智能的生成样式研究[J]. 现代防御技术, 2020, 48(5): 44-49.

XU Rui-ming. Research on Generation Style of UAV Cluster Intelligence[J]. Modern Defense Technology, 2020, 48(5): 44-49.

参考文献

[1] 张昊.美国无人机协同作战研究[J].飞航导弹,2017(8):12-16,21.
ZHANG Hao.Research on the United States UAV Cooperative Operation[J].Winged Missiles Journal,2017(8):12-16,21.
[2] 许彪,张宇,王超.美军无人系统蜂群技术发展现状与趋势分析[J] .飞航导弹,2018(3):36-39.
XU Biao,ZHANG Yu,WANG Chao.Analysis of the Current Situation and Trend of the Development of U.S.Unmanned System Bee Colony Technology[J].Winged Missiles Journal,2018(3):36-39.
[3] 王凤娟,姜淑凤,单永瑞,等.群智能优化算法的研究与分析[J].信息通信,2018(10):1-2.
WANG Feng-juan,JIANG Shu-feng,SHAN Yong-rui,et al.Research and Analysis of Swarm Intelligence Optimization Algorithm[J].Information & Communications,2018(10):1-2.
[4] 梁晓龙,孙强,尹忠海,等.大规模无人系统集群智能控制方法综述[J] .计算机应用研究,2015,32(1):11-16.
LIANG Xiao-long,SUN Qiang,YIN Zhong-hai,et al.Review on Large-Scale Unmanned System Swarm Intelligence Control Method[J].Application Research of Computers,2015,32(1):11-16.
[5] 冯肖雪,潘峰,梁彦,等.群集智能优化算法及应用[M].北京:科学出版社,2018.
FENG Xiao-xue,PAN Feng,LIANG Yan,et al.Swarm Intelligence Optimization Algorithm and Its Application[M].Beijing:Science Press,2018.
[6] 申海.集群智能及其应用[M].北京:科学出版社,2019.
SHEN Hai.Swarm Intelligence and Its Application[M].Beijing:Science Press,2019.
[7] 李建军.基于群体智能的多AUV协同任务分配方法研究[D].哈尔滨:哈尔滨工程大学,2018.
LI Jian-jun.Research on Multi-AUV Collaborative Task Allocation Method Based on Swarm Intelligence[D].Harbin:Harbin Engineering University,2018.
[8] 王万森.人工智能原理及其应用[M].北京:电子工业出版社,2014.
WANG Wan-Sen.Principle and Application of Artificial Intelligence[M].Beijing:Electronic Industry Press,2014.
[9] 王红卫,祁超.基于层次任务网络规划的应急响应决策理论与方法[M].北京:科学出版社,2015.
WANG Hong-wei,QI Chao.Emergency Response Decision Theory and Method Based on Hierarchical Task Network Planning[M].Beijing:Science Press,2015.
[10] 程子光,冯亚军,尹康银,等.自然计算在求解网络优化部署问题中的比较[J].空军预警学院学报,2019,33(5):367-371.
CHENG Zi-guang,FENG Ya-jun,YIN Kang-yin,et al.Comparison of Natural Computations in Solving Network Optimization Deployment[J].Journal of Air Force Early Warning Academy,2019,33(5):367-371.
[11] 叶春明,李永林,刘长平.新型仿生群智能算法及其生产调度应用[M].北京:科学出版社,2015.
YE Chun-ming,LI Yong-lin,LIU Chang-ping.New Bionic Swarm Intelligence Optimization Algorithm and Its Application in Production Scheduling[M].Beijing:Science Press,2015.
[12] 王飞跃.平行系统方法与复杂系统的管理和控制[J].控制与决策,2004,19(5):485-489,514 .
WANG Fei-yue.Parallel System Methods for Management and Control of Complex Systems[J].Control and Decision,2004,19(5):485-489,514 .
[13] 陈龙,宇文旋,曹东璞,等.平行无人系统[J].无人系统技术,2018,1(1):23-37.
CHEN Long,YU Wen-xuan,CAO Dong-pu,et al.Parallel Unmanned System[J].Unmanned Systems Technology,2018,1(1):23-37.
[14] 沈震,刘雅婷,董西松,等.平行机群:概念、框架与应用[J].指挥与控制学报,2018,4(3):201-212.
SHEN Zhen,LIU Ya-ting,DOND Xi-song,et al.Parallel Multi-UAV System:Concepts,Framework and Applications[J].Journal of Command and Control,2018,4 (3):201-212.
[15] 邵壮.多无人机编队路径规划与队形控制技术研究[D].西安:西北工业大学,2016.
SHAO Zhuang.Research on Formation Path Planning and Formation Control Technology of Multiple UAVs[D].Xi'an:Northwestern Polytechnical University,2016.
[16] 韩亮,任章,董希旺,等.多无人机协同控制方法及应用研究[J].导航定位与授时,2018,5(4):1-7.
HAN Liang,REN Zhang,DONG Xi-wang,et al.Research on Cooperative Control Method and Application for Multiple Unmanned Aerial Vehicles[J].Navigation Position & Timing,2018,5(4):1-7.
[17] 邱华鑫,段海滨.从鸟群群集飞行到无人机自主集群编队[J].工程科学学报,2017,39(3):317-322.
QIU Hua-xin,DUAN Hai-bin.From Collective Flight in Bird Flocks to Unmanned Aerial Vehicle Autonomous Swarm Formation [J].Chinese Journal of Engineering,2017,39(3):317-322.
[18] 杨万海.多传感器数据融合及其应用[M].西安:西安电子科技大学出版社,2004.
YANG Wan-hai.Multisensor Data Fusion and Its Application[M].Xi'an:Xidian University Press,2004.
[19] 杨晨,张少卿,孟光磊.多无人机协同任务规划研究[J].指挥与控制学报,2018,4(3):234-248.
YANG Chen,ZHANG Shao-qing,MENG Guang-lei.Multi-UAV Cooperative Mission Planning[J].Journal of Command and Control,2018,4(3):234-248.

无人机集群智能的生成样式研究

Research on Generation Style of UAV Cluster Intelligence

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