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基于搜索意图交互的无人机集群协同搜索算法

王宁 李哲 梁晓龙 侯岳奇 吴傲

王宁, 李哲, 梁晓龙, 等 . 基于搜索意图交互的无人机集群协同搜索算法[J]. 北京航空航天大学学报, 2022, 48(3): 454-463. doi: 10.13700/j.bh.1001-5965.2020.0602
引用本文: 王宁, 李哲, 梁晓龙, 等 . 基于搜索意图交互的无人机集群协同搜索算法[J]. 北京航空航天大学学报, 2022, 48(3): 454-463. doi: 10.13700/j.bh.1001-5965.2020.0602
WANG Ning, LI Zhe, LIANG Xiaolong, et al. Cooperative search algorithm for UAV swarm based on search intention interaction[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(3): 454-463. doi: 10.13700/j.bh.1001-5965.2020.0602(in Chinese)
Citation: WANG Ning, LI Zhe, LIANG Xiaolong, et al. Cooperative search algorithm for UAV swarm based on search intention interaction[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(3): 454-463. doi: 10.13700/j.bh.1001-5965.2020.0602(in Chinese)

基于搜索意图交互的无人机集群协同搜索算法

doi: 10.13700/j.bh.1001-5965.2020.0602
基金项目: 

国家自然科学基金 61703427

国防创新特区项目 

“十三五”装备预研共用技术项目 

详细信息
    通讯作者:

    李哲, E-mail: kongyanshi@126.com

  • 中图分类号: V279+.3;V249.122

Cooperative search algorithm for UAV swarm based on search intention interaction

Funds: 

National Natural Science Foundation of China 61703427

National Defense Innovation Special Zone Project 

"13th Five Year Plan"Equipment Pre-research Sharing Technology Project 

More Information
  • 摘要:

    针对无先验信息条件下无人机集群的协同搜索问题,提出一种以覆盖率为引导,以机间安全距离、通信距离、偏航角调整及搜索边界等为约束的无人机集群协同搜索算法。通过建立环境地图矩阵对任务区域进行描述,进一步定义环境地图更新算子实现搜索过程中环境地图的快速更新。设计了集群协同搜索任务的回报函数,采用粒子群算法进行求解,得到每架无人机在已知环境地图下的最优决策,即决策意图。每架无人机在获取其他成员决策意图的基础上重新进行决策,实现协同决策。针对不同规模集群提出了集中式和分布式2种协同决策方案。仿真结果表明,所提算法能够对存在未知威胁的不规则任务区域进行有效覆盖搜索,覆盖率远高于不进行协同决策的个体决策方法。

     

  • 图 1  UAV集群协同搜索示意图

    Figure 1.  Schematic diagram of UAV swarm collaborative search

    图 2  任务区域栅格化

    Figure 2.  Rasterized task area

    图 3  UAVi航路预测图

    Figure 3.  UAVi route forecast chart

    图 4  UAV探测区域栅格化

    Figure 4.  Rasterized UAV detection area

    图 5  环境地图矩阵更新流程

    Figure 5.  Update process of environment map matrix

    图 6  决策环境信息矩阵产生流程

    Figure 6.  Decision environment information matrix generation process

    图 7  UAV集群环境地图矩阵更新流程

    Figure 7.  UAV swarm enviornment map update process

    图 8  集中式意图交互

    Figure 8.  Centralized intention interaction

    图 9  分布式意图交互

    Figure 9.  Distributed intention interaction

    图 10  三种搜索算法仿真结果

    Figure 10.  Simulation results of three search algorithms

    图 11  三种搜索算法覆盖率变化曲线

    Figure 11.  Coverage change curves of three search algorithms

    图 12  10架UAV集群协同搜索仿真结果

    Figure 12.  Collaborative search simulation results for swarm with 10 UAVs

    图 13  集群中机间最小距离曲线

    Figure 13.  Curve of minimum distance between UAVs of swarm

    图 14  覆盖率变化曲线

    Figure 14.  Change curve of coverage

    表  1  环境地图融合算子运算规则

    Table  1.   Environmental map fusion operator operation rules

    gi(k) gj(k)
    0 -1 +1
    0 0 0 0
    -1 0 -1 +1
    +1 0 +1 +1
    下载: 导出CSV

    表  2  算法参数

    Table  2.   Algorithm parameters

    参数 ω1 ω2 ω3 ω4 ω5 ds/m dc/m
    数值 0.3 0.2 0.2 0.1 0.2 20 500
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-10-26
  • 录用日期:  2021-01-15
  • 刊出日期:  2022-03-20

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