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基于空间两点的视觉自主着陆导引算法设计

魏祥灰 唐超颖 王彪

魏祥灰, 唐超颖, 王彪等 . 基于空间两点的视觉自主着陆导引算法设计[J]. 北京航空航天大学学报, 2019, 45(2): 357-365. doi: 10.13700/j.bh.1001-5965.2018.0285
引用本文: 魏祥灰, 唐超颖, 王彪等 . 基于空间两点的视觉自主着陆导引算法设计[J]. 北京航空航天大学学报, 2019, 45(2): 357-365. doi: 10.13700/j.bh.1001-5965.2018.0285
WEI Xianghui, TANG Chaoying, WANG Biaoet al. Visual guidance algorithm design for autonomous landing based on two points in space[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(2): 357-365. doi: 10.13700/j.bh.1001-5965.2018.0285(in Chinese)
Citation: WEI Xianghui, TANG Chaoying, WANG Biaoet al. Visual guidance algorithm design for autonomous landing based on two points in space[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(2): 357-365. doi: 10.13700/j.bh.1001-5965.2018.0285(in Chinese)

基于空间两点的视觉自主着陆导引算法设计

doi: 10.13700/j.bh.1001-5965.2018.0285
基金项目: 

南京航空航天大学研究生创新基地(实验室)开放基金-中央高校基本科研业务费专项资金 kfjj20170302

详细信息
    作者简介:

    魏祥灰  女, 硕士研究生。主要研究方向:无人机视觉导引

    唐超颖  女, 博士, 副教授, 硕士生导师。主要研究方向:导引控制与图像处理

    王彪  男, 博士, 副教授, 硕士生导师。主要研究方向:飞行器控制与视觉导引

    通讯作者:

    王彪, E-mail: wangbiao@nuaa.edu.cn

  • 中图分类号: V249.3

Visual guidance algorithm design for autonomous landing based on two points in space

Funds: 

Graduate Innovation Center in NUAA-the Fundamental Research Funds for the Central Universities kfjj20170302

More Information
  • 摘要:

    为提高无人机着陆效率,从着陆速度向量场和导引律设计两方面研究改进。首先,基于椭圆设计速度向量场,实现飞行路程更短、机动性能要求更低的着陆轨迹。然后,基于像素坐标系与机体坐标系的关系,设计无人机的航迹方位角指令;以椭圆切线方向为参考,结合合作矢量特征,设计航迹倾斜角指令;利用图像信息,设计速度大小指令。最后,理论比较了传统轨迹与提出轨迹对方向机动性性能的要求,给出了轨迹参数与无人机方向机动性性能的关系。利用Simulink搭建系统仿真平台,计算满足要求的合作矢量特征。结果表明,无人机以曲线轨迹准确软着陆到目标,满足实际运用的需要。

     

  • 图 1  椭圆弧示意图

    Figure 1.  Schematic diagram of elliptic arc

    图 2  速度向量场示意图

    Figure 2.  Schematic diagram of velocity vector field

    图 3  本文导引律的结构框图

    Figure 3.  Structure diagram of proposed guidance law

    图 4  机体坐标系与像素坐标系的关系示意图

    Figure 4.  Schematic diagram of relationship between body coordinate system and image coordinate system

    图 5  无人机与合作特征的空间关系

    Figure 5.  Spatial relationship between UAV and cooperative characteristics

    图 6  β与图像信息之间的关系示意图

    Figure 6.  Schematic diagram of relationship between β and image information

    图 7  着陆轨迹的比较

    Figure 7.  Comparison of landing trajectory

    图 8  系统仿真平台结构框图

    Figure 8.  Structure diagram of system simulation platform

    图 9  无人机着陆过程仿真示意图

    Figure 9.  Schematic diagram of UAV landing process simulation

    图 10  导引指令随时间的变化

    Figure 10.  Variation of guidance command with time

    图 11  响应随时间的变化

    Figure 11.  Variation of response with time

    图 12  β角分析

    Figure 12.  β angle analysis

    图 13  α角分析

    Figure 13.  α angle analysis

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出版历程
  • 收稿日期:  2018-05-21
  • 录用日期:  2018-09-19
  • 刊出日期:  2019-02-20

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