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基于逃逸角的多ASV微分博弈协同围捕方法

杨惠珍 李建国 吴天宇 王子江 杨钧

杨惠珍, 李建国, 吴天宇, 等. 基于逃逸角的多ASV微分博弈协同围捕方法[J]. 水下无人系统学报, 2024, 32(4): 730-738 doi: 10.11993/j.issn.2096-3920.2023-0142
引用本文: 杨惠珍, 李建国, 吴天宇, 等. 基于逃逸角的多ASV微分博弈协同围捕方法[J]. 水下无人系统学报, 2024, 32(4): 730-738 doi: 10.11993/j.issn.2096-3920.2023-0142
YANG Huizhen, LI Jianguo, WU Tianyu, WANG Zijiang, YANG Jun. Cooperative Hunting Method for Multiple ASVs Using Differential Games Based on Escape Angle[J]. Journal of Unmanned Undersea Systems, 2024, 32(4): 730-738. doi: 10.11993/j.issn.2096-3920.2023-0142
Citation: YANG Huizhen, LI Jianguo, WU Tianyu, WANG Zijiang, YANG Jun. Cooperative Hunting Method for Multiple ASVs Using Differential Games Based on Escape Angle[J]. Journal of Unmanned Undersea Systems, 2024, 32(4): 730-738. doi: 10.11993/j.issn.2096-3920.2023-0142

基于逃逸角的多ASV微分博弈协同围捕方法

doi: 10.11993/j.issn.2096-3920.2023-0142
基金项目: 水下信息与控制重点实验室基金项目资助(2021-JCJQ-LB-030-03).
详细信息
    作者简介:

    杨惠珍(1974-), 女, 博士, 研究员, 主要研究方向为水下机器人控制与仿真、多机器人系统

  • 中图分类号: TJ630.1; U664.82

Cooperative Hunting Method for Multiple ASVs Using Differential Games Based on Escape Angle

  • 摘要: 针对多个自主水面航行器(ASV)围捕单个主动逃逸的对抗性目标问题, 利用微分博弈理论建立了多ASV协同围捕问题博弈模型, 在含有距离项的支付函数中引入由逃逸角构成的合围项, 从而降低目标中途逃逸的概率; 然后将围捕问题转换为求解可实现策略的优化问题, 利用粒子群优化(PSO)算法求解满足纳什均衡的最优策略, 仿真和湖上试验结果均证明了基于PSO的微分博弈围捕算法的有效性。

     

  • 图  1  二维直角坐标系追逃几何模型

    Figure  1.  Two-dimensional cartesian coordinate system pursuit-and-escape geometry

    图  2  协同围捕数量关系图

    Figure  2.  Diagram of the number of coordinated round-ups

    图  3  极坐标系下逃逸角示意图

    Figure  3.  Schematic diagram of the escape angle in a polar coordinate system

    图  4  围捕者使邻居逃逸角“均匀化”示意图

    Figure  4.  Schematic diagram of the round-up "homogenizing" the escape angle of the neighbor

    图  5  基于PSO的围捕路径流程图

    Figure  5.  Flow chart of round-up path based on PSO

    图  6  文献[21]算法的围捕仿真实验图

    Figure  6.  Round-up simulation experiment diagram of the algorithm in Ref [21]

    图  7  文中改进算法的围捕仿真实验图

    Figure  7.  Round-up simulation experiment of the improved algorithm

    图  8  不同算法的逃逸角曲线

    Figure  8.  Escape angle curves of different algorithms

    图  9  不同算法追逃最小距离对比图

    Figure  9.  Comparison chart of the minimum distance of pursuit and escape

    图  10  围捕实验平台总体方案

    Figure  10.  Overall scheme of the round-up experimental platform

    图  11  ASV外观

    Figure  11.  Exterior of the ASV

    图  12  ASV Ardupilot底层控制代码架构

    Figure  12.  The underlying control code architecture of the Ardupilot of ASV

    图  13  协同围捕信息转换

    Figure  13.  Collaborative round-up information transformation

    图  14  实际围捕过程图

    Figure  14.  Diagram of the actual round-up proces

    表  1  ASV性能参数表

    Table  1.   Performance parameters of the ASV

    性能指标数值单位
    外观尺寸510×180×115mm·mm·mm
    最大速度2.2m/s
    最大航时50min
    电池容量5 100mA·h
    最大续航里程4.5km
    最大通信距离1.2km
    下载: 导出CSV
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    HU Y Y, ZHANG L, XIA H, et al. Cooperative capture of maneuvering targets with incomplete information based on differential game[J]. Acta Aeronautica ET Astronautica Sinica, 2022, 43(S1): 53-64.
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出版历程
  • 收稿日期:  2023-11-09
  • 修回日期:  2023-12-25
  • 录用日期:  2024-02-07
  • 网络出版日期:  2024-03-15

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