甄子洋

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教授

招生学科专业:
控制科学与工程 -- 【招收博士、硕士研究生】 -- 自动化学院
兵器科学与技术 -- 【招收硕士研究生】 -- 自动化学院
电子信息 -- 【招收博士、硕士研究生】 -- 自动化学院

性别:男

毕业院校:南京航空航天大学

学历:南京航空航天大学

学位:工学博士学位

所在单位:自动化学院

办公地点:通信地址:南京市江宁区将军大道29号 南航自动化学院
邮编:211106

联系方式:025-84892301-8003

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Offense-defense confrontation decision making for dynamic UAV swarm versus UAV swarm

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所属单位:自动化学院

发表刊物:PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING

关键字:Unmanned aerial vehicles swarm versus swarm UAV combat offense-defense confrontation target allocation decision swarm motion decision

摘要:This paper studies a dynamic swarm versus swarm unmanned aerial vehicle (UAV) combat problem and proposes a self-organized offense-defense confrontation decision-making (ODCDM) algorithm. This ODCDM algorithm adopts the distributed architecture to account for real-time implementation, where each UAV is treated as an agent and able to solve its local decision problem through the information exchange with neighbors. At each decision making step, the swarm seeks an optimal target allocation scheme and each UAV further selects the corresponding behavioral rules, leading to emergent offensive and defensive behaviors. Therefore, the offense-defense confrontation decision-making process is divided into the target allocation decision based on distributed consensus-based auction algorithm (CBAA) and social-force-based swarm motion decision. An offense-defense preference is introduced to the target allocation optimization model, providing the tactics options for UAV to adopt more offensive or more defensive posture. On the basis of classic collective behaviors of cohesion, separation and alignment, a combat stimulus is considered to drive UAV towards the assigned target. Finally, simulation experiments are carried out to verify the effectiveness of the ODCDM algorithm, and analyze the influences of the external deployment and internal tactics on the combat results.

ISSN号:0954-4100

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发表时间:2019-12-01

合写作者:Xing, Dongjing,龚华军

通讯作者:甄子洋