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未知环境下无人机集群协同区域搜索算法

侯岳奇 梁晓龙 何吕龙 刘流

侯岳奇, 梁晓龙, 何吕龙, 等 . 未知环境下无人机集群协同区域搜索算法[J]. 北京航空航天大学学报, 2019, 45(2): 347-356. doi: 10.13700/j.bh.1001-5965.2018.0230
引用本文: 侯岳奇, 梁晓龙, 何吕龙, 等 . 未知环境下无人机集群协同区域搜索算法[J]. 北京航空航天大学学报, 2019, 45(2): 347-356. doi: 10.13700/j.bh.1001-5965.2018.0230
HOU Yueqi, LIANG Xiaolong, HE Lyulong, et al. Cooperative area search algorithm for UAV swarm in unknown environment[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(2): 347-356. doi: 10.13700/j.bh.1001-5965.2018.0230(in Chinese)
Citation: HOU Yueqi, LIANG Xiaolong, HE Lyulong, et al. Cooperative area search algorithm for UAV swarm in unknown environment[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(2): 347-356. doi: 10.13700/j.bh.1001-5965.2018.0230(in Chinese)

未知环境下无人机集群协同区域搜索算法

doi: 10.13700/j.bh.1001-5965.2018.0230
基金项目: 

国家自然科学基金 61472443

国家自然科学基金 61703427

陕西省自然科学基础研究计划 2017JQ6035

详细信息
    作者简介:

    侯岳奇  男, 硕士研究生。主要研究方向:航空集群智能决策

    梁晓龙  男, 博士, 教授, 硕士生导师。主要研究方向:航空集群指挥与控制、智能系统、空管智能化

    何吕龙  男, 博士研究生。主要研究方向:航空集群编队控制

    刘流  男, 硕士研究生。主要研究方向:航空集群编队控制

    通讯作者:

    梁晓龙, E-mail: afeu_lxl@sina.com

  • 中图分类号: V279+.3;V249.122

Cooperative area search algorithm for UAV swarm in unknown environment

Funds: 

National Natural Science Foundation of China 61472443

National Natural Science Foundation of China 61703427

Natrual Science Basic Research Plan in Shaanxi Province of China 2017JQ6035

More Information
  • 摘要:

    针对无人机集群在无先验信息的未知环境中协同搜索的问题,提出了一种以覆盖率为实时搜索奖励的无人机集群协同区域搜索算法。首先建立覆盖分布地图(CDM)来描述任务环境,并采用Hadamard积实现CDM的快速更新,继而基于CDM计算覆盖率来定量描述实时搜索效果。将无人机集群视为一个控制系统,基于分布式模型预测控制理论建立系统的预测模型,并将预测周期内最大覆盖率增量设为奖励函数,采用差分进化算法进行求解,得到最优解作为系统的最优输入。仿真结果表明,所提算法能够对区域进行覆盖搜索,在出现突发情况时,覆盖率远高于平行搜索方法。

     

  • 图 1  UAV集群协同搜索示意图

    Figure 1.  Schematic diagram of UAV swarm cooperative search

    图 2  任务区域栅格化

    Figure 2.  Mission area rasterization

    图 3  H步预测航路图

    Figure 3.  H step route prediction

    图 4  覆盖分布地图更新流程

    Figure 4.  Update process of coverage distribution map

    图 5  区域Ψ栅格化

    Figure 5.  Region Ψ rasterization

    图 6  基于Hadamard积的地图信息融合示意图

    Figure 6.  Schematic diagram of map information fusion based on Hadamard product

    图 7  DMPC框架示意图

    Figure 7.  Schematic diagram of DMPC framework

    图 8  MPCi决策流程

    Figure 8.  Decision-making process of MPCi

    图 9  3种搜索方法的仿真结果

    Figure 9.  Simulation results of three search methods

    图 10  3种搜索方法的覆盖率变化曲线

    Figure 10.  Coverage rate changing curve of three search methods

    图 11  本文算法仿真结果

    Figure 11.  Simulation result of proposed algorithm

    图 12  本文算法覆盖率变化曲线

    Figure 12.  Coverage rate changing curve of proposed algorithm

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出版历程
  • 收稿日期:  2018-04-25
  • 录用日期:  2018-10-15
  • 网络出版日期:  2019-02-20

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