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基于环流斥力势场的改进APF导弹航路规划

卢发兴 戴秋洋 许俊飞 贾正荣

卢发兴, 戴秋洋, 许俊飞, 等. 基于环流斥力势场的改进APF导弹航路规划[J]. 航空动力学报, 2023, 38(9):2288-2298 doi: 10.13224/j.cnki.jasp.20210722
引用本文: 卢发兴, 戴秋洋, 许俊飞, 等. 基于环流斥力势场的改进APF导弹航路规划[J]. 航空动力学报, 2023, 38(9):2288-2298 doi: 10.13224/j.cnki.jasp.20210722
LU Faxing, DAI Qiuyang, XU Junfei, et al. Improved APF missile route planning based on circulation repulsion potential field[J]. Journal of Aerospace Power, 2023, 38(9):2288-2298 doi: 10.13224/j.cnki.jasp.20210722
Citation: LU Faxing, DAI Qiuyang, XU Junfei, et al. Improved APF missile route planning based on circulation repulsion potential field[J]. Journal of Aerospace Power, 2023, 38(9):2288-2298 doi: 10.13224/j.cnki.jasp.20210722

基于环流斥力势场的改进APF导弹航路规划

doi: 10.13224/j.cnki.jasp.20210722
详细信息
    作者简介:

    卢发兴(1974-),男,教授、博士生导师,博士,主要从事智能武器控制和多智能体协同控制方面的研究

    通讯作者:

    戴秋洋(1999-),男,硕士生,主要从事多智能体协同控制方面的研究。E-mail:1638443928@qq.com

  • 中图分类号: V219

Improved APF missile route planning based on circulation repulsion potential field

  • 摘要:

    为解决人工势场(artificial potential field,APF)方法容易陷入局部最小值的问题,提出基于环流斥力势场的改进APF航路规划方法(改进APF方法),改变斥力势场方向使其变成围绕障碍物的环流,并结合导弹由航路点控制的特点,进一步由约束法和切线法得到导弹飞行航路点。在不同场景下分别采用传统APF方法与改进APF方法进行航路规划求解,以及使用切线法和约束法进行导弹航路点求解。结果表明:改进APF方法有效提高可解概率,能够在多边形障碍密集、障碍边界与导弹航向垂直的情况下得到航路。同时,相比传统APF方法,改进APF方法生成的航路较平滑。对于导弹航路点求解,切线法和约束法所得到的导弹航路航程相差不大,但约束法的解算时间较短且生成航点数量较少,而切线法的安全性能较好。

     

  • 图 1  传统APF方法的势场与航路(振荡)

    Figure 1.  Potential field and route of traditional APF method (oscillation)

    图 2  传统APF方法的势场与航路(无解)

    Figure 2.  Potential field and route of traditional APF method (no solution)

    图 3  环流斥力势场与航路

    Figure 3.  Circulation repulsion potential field and route

    图 4  考虑障碍物威胁等级的航路规划

    Figure 4.  Route planning considering obstacle threat level

    图 5  改进APF方法流程图

    Figure 5.  Flow chart of improved APF method

    图 6  约束法流程图

    Figure 6.  Flow chart of constraint method

    图 7  切线法流程图

    Figure 7.  Flow chart of tangent method

    图 8  场景A

    Figure 8.  Scenario A

    图 9  场景B

    Figure 9.  Scenario B

    图 10  场景C

    Figure 10.  Scenario C

    图 11  场景D

    Figure 11.  Scenario D

    图 12  障碍之间的合势场比较

    Figure 12.  Comparison of potential fields between obstacles

    图 13  场景E

    Figure 13.  Scenario E

    图 14  场景F

    Figure 14.  Scenario F

    表  1  航路振荡指标对比

    Table  1.   Route oscillation index contrast

    场景H
    传统APF方法改进APF方法
    C29.44104.1008
    D34.12257.8445
    下载: 导出CSV

    表  2  耗时对比

    Table  2.   Time contrast

    场景耗时/s
    传统APF方法改进APF方法
    C0.64930.5708
    D0.33990.2527
    下载: 导出CSV

    表  3  图13(a)关键航路点

    Table  3.   Key waypoints for Fig.13(a)

    x−1008.966141.402499.5412
    y0−1.1006−33.7872−0.3534
    下载: 导出CSV

    表  4  图13(b)关键航路点

    Table  4.   Key waypoints for Fig.13(b)

    x−10019.190644.704778.921099.54118
    y0−6.2876−36.7713−16.3532−0.35337
    下载: 导出CSV

    表  5  图14(a)关键航路点

    Table  5.   Key waypoints for Fig.14(a)

    x−100−40.6761−26.043212.8005
    y03.191016.76339.3463
    x29.324842.886462.660299.64576
    y−1.8098−16.1883−13.94040.082511
    下载: 导出CSV

    表  6  图14(b)关键航路点

    Table  6.   Key waypoints for Fig.14(b)

    x−100−48.4025−34.15648.7776
    y00.085514.164710.5468
    x39.825177.851599.6458
    y−13.3379−7.50130.0825
    下载: 导出CSV

    表  7  导弹航程对比

    Table  7.   Missile range contrast

    场景航路距离
    切线法约束法
    E224.55194225.22698
    F218.07200214.71717
    下载: 导出CSV

    表  8  解算时间对比

    Table  8.   Solving time comparison

    场景解算时间/s
    切线法约束法
    E0.12100.0829
    F0.10660.0715
    下载: 导出CSV
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  • 收稿日期:  2021-12-22
  • 网络出版日期:  2022-12-16

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