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多目标群多基地多无人机协同任务规划
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  • 英文篇名:Collaborative Mission Planning of Multi-target Group Multi-base and Multi-UAV
  • 作者:刘畅 ; 谢文俊 ; 张鹏 ; 郭庆
  • 英文作者:LIU Chang;XIE Wenjun;ZHANG Peng;GUO Qing;Equipment Management and UAV Engineering College, Air Force Engineering University;
  • 关键词:任务规划 ; 周期性快速搜索遗传算法 ; 无人机 ; 共同分配
  • 英文关键词:mission planning;;periodic fast search genetic algorithm;;UAV;;common assignment
  • 中文刊名:DJZD
  • 英文刊名:Journal of Projectiles,Rockets,Missiles and Guidance
  • 机构:空军工程大学装备管理与无人机工程学院;
  • 出版日期:2018-11-20 11:19
  • 出版单位:弹箭与制导学报
  • 年:2019
  • 期:v.39;No.189
  • 基金:航空科学基金(20165596025)资助
  • 语种:中文;
  • 页:DJZD201901025
  • 页数:6
  • CN:01
  • ISSN:61-1234/TJ
  • 分类号:125-130
摘要
针对多目标群多基地多无人机协同任务规划问题,提出了一种周期性快速搜索遗传算法。以侦察任务为背景,将共同分配策略引入到任务规划中来,构建了多无人机协同侦察任务规划决策数学模型,并运用提出的周期性快速搜索遗传算法求解多无人机协同侦察任务规划问题。通过仿真算例,验证了模型的有效性和算法的合理性,与单亲遗传算法、传统遗传算法求解相比,周期性快速搜索遗传算法求解效率快且精度高。
        Aimed the problem of collaborative mission planning of multi-target group multi-base multi-UAV, a periodic fast search genetic algorithm(PFSGA) is proposed. For the task of reconnaissance, this paper introduces the common assignment strategy into the mission planning, builds the multi-UAV collaborative reconnaissance mission planning mathematical model and applies the PFSGA to solve the multi-UAV collaborative reconnaissance mission planning problem. Simulation example verified the validity of the modal and the rationality of the algorithm. The comparison with the single parent genetic algorithm and the traditional genetic algorithm, the PFSGA is more efficient and accurate.
引文
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