﻿ 基于空间两点的视觉自主着陆导引算法设计<sup>*</sup>
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Visual guidance algorithm design for autonomous landing based on two points in space
WEI Xianghui, TANG Chaoying, WANG Biao
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Received: 2018-05-21; Accepted: 2018-09-19; Published online: 2018-10-10 16:27
Foundation item: Fundation of Graduate Innovation Center in NUAA-the Fundamental Research Funds for the Central Universities (kfjj20170302)
Corresponding author. WANG Biao, E-mail: wangbiao@nuaa.edu.cn
Abstract: In order to increase the landing efficiency, improvements are made in two aspects:landing velocity vector field and guidance law design. Landing velocity vector field is designed based on ellipse curve for the requirements of shorter flight path and less maneuverability. Meanwhile, the flight path azimuth angle command is generated based on the relationship between the image coordinate system and the body-fixed frame. With reference to the tangential direction of the ellipse, the flight path elevation angle is tuned and combined with the cooperative vector features. Speed command is calculated using image information. Finally, the requirements of the traditional trajectory and the proposed trajectory on the directional maneuverability are compared in theory. The relationship between the trajectory parameters and the UAV turning performance is then shown. The system simulation platform is built based on Simulink, and the required cooperative vector is calculated. The results show that the UAV accurately lands on the target with curved trajectory, which meets the needs in practical applications.
Keywords: VTOL UAV     autonomous landing     vision-based guidance law     velocity vector field     turning maneuver performance

1 速度向量场的设计与分析

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 图 1 椭圆弧示意图 Fig. 1 Schematic diagram of elliptic arc

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x=0以及x=2b轴上任意点，与C1点作椭圆弧，建立目标着陆点周围的速度向量场(见图 2)。

 图 2 速度向量场示意图 Fig. 2 Schematic diagram of velocity vector field

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2 导引律的设计

 图 3 本文导引律的结构框图 Fig. 3 Structure diagram of proposed guidance law
2.1 图像特征与速度方向的关系

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 图 4 机体坐标系与像素坐标系的关系示意图 Fig. 4 Schematic diagram of relationship between body coordinate system and image coordinate system

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Rbc表达式为

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 图 5 无人机与合作特征的空间关系 Fig. 5 Spatial relationship between UAV and cooperative characteristics

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M(xM, yM)坐标表达式为

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 图 6 β与图像信息之间的关系示意图 Fig. 6 Schematic diagram of relationship between β and image information

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2.2 图像特征与速度大小的关系

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3 仿真验证与分析 3.1 与传统方法比较分析

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 图 7 着陆轨迹的比较 Fig. 7 Comparison of landing trajectory

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3.2 系统仿真验证

 图 8 系统仿真平台结构框图 Fig. 8 Structure diagram of system simulation platform

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 图 9 无人机着陆过程仿真示意图 Fig. 9 Schematic diagram of UAV landing process simulation

 图 10 导引指令随时间的变化 Fig. 10 Variation of guidance command with time

 图 11 响应随时间的变化 Fig. 11 Variation of response with time

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 图 12 β角分析 Fig. 12 β angle analysis
 图 13 α角分析 Fig. 13 α angle analysis

4 结论

1) 突破传统直角型的转弯方式，设计曲线型速度向量场，导引垂直起降无人机曲线着陆，保证末端约束的前提下，提高无人机的着陆效率。

2) 避免传统导引算法中的位置解算，直接建立图像信息与速度指令之间的关系，避免了位置解算引入的计算量和误差，提高计算效率。

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#### 文章信息

WEI Xianghui, TANG Chaoying, WANG Biao

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

Journal of Beijing University of Aeronautics and Astronsutics, 2019, 45(2): 357-365
http://dx.doi.org/10.13700/j.bh.1001-5965.2018.0285