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Expert Knowledge-Assisted Drone Combat Strategy via Intention Interpretation

  • Xindi Wang
  • , Hao Liu*
  • , Dawei Liu
  • , Ming Cheng
  • , Chenguang Liu
  • , Xiaoguang Wang
  • , Mutian Guo
  • *此作品的通讯作者
  • Beihang University
  • China Research and Development Academy of Machinery Equipment
  • Norinco Group Air Ammunition Research Institute

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In this paper, a drone game strategy generation model is designed in a denied environment. A typical nonlinear model of drone formation dynamics is first constructed. A behavior prediction algorithm based on neural network is then utilized to predict the trajectory and behavior characteristics of the attack drones, and a neural network algorithm achieves intelligent interpretation of the attack drones intention based on the result of the prediction. A game strategy generation algorithm assisted by expert knowledge and game experience library is finally proposed using the result of the intention interpretation. These algorithms overcome the difficulty of obtaining the game strategy under the deceptive and elusive characteristics of attacking drones and realize high real-time and pertinence of decision-making. Simulation results of typical scenarios are provided to verify the effectiveness of the proposed algorithm model.

源语言英语
主期刊名2023 42nd Chinese Control Conference, CCC 2023
出版商IEEE Computer Society
8143-8147
页数5
ISBN(电子版)9789887581543
DOI
出版状态已出版 - 2023
活动42nd Chinese Control Conference, CCC 2023 - Tianjin, 中国
期限: 24 7月 202326 7月 2023

出版系列

姓名Chinese Control Conference, CCC
2023-July
ISSN(印刷版)1934-1768
ISSN(电子版)2161-2927

会议

会议42nd Chinese Control Conference, CCC 2023
国家/地区中国
Tianjin
时期24/07/2326/07/23

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