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浙江大学学报(工学版)
Journal of ZheJiang University (Engineering Science)  2021, Vol. 55 Issue (1): 96-108    DOI: 10.3785/j.issn.1008-973X.2021.01.012
    
Dynamic tracking and precise landing of UAV based on visual magnetic guidance
Yan-wei ZHAO(),Jian ZHANG,Xian-ming ZHOU,Geng-yu WU
College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310058, China
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Abstract  

The tracking control strategy of follow-up visual tracking and the method of obtaining high precision relative pose of UAV based on vision and magnetic guidance were proposed in order to solve the problem that UAV can easily lose the target when tracking the ground dynamic target through vision and the positioning accuracy is poor due to serious imaging distortion and unstable picture during landing. A new beacon pattern was designed for UAV visual recognition in order to obtain the target orientation in the tracking process. The recognition speed can reach 5 ms/frame, and real-time tracking is completed by follow-up visual tracking. The magnetic source was set on the dynamic target in the process of landing. The magnetic field characteristics were detected by UAV and the relative position was calculated by BP neural network. A parallel line feature was set in the beacon pattern to assist the visual calculation of the relative angle when the camera was close to the target. The landing can be completed by corresponding motion control after obtaining the relative pose of UAV. The experimental results show that the method can achieve a stable and reliable track and high anti-jamming ability, and can reach high precision with less than 2 cm during landing.

Key words： visual tracking      visual beacon      magnetic guidance      neural network      pose calculation     
Received: 09 September 2020      Published: 05 January 2021
CLC:  TP 242  
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Yan-wei ZHAO
Jian ZHANG
Xian-ming ZHOU
Geng-yu WU
Cite this article:

Yan-wei ZHAO,Jian ZHANG,Xian-ming ZHOU,Geng-yu WU. Dynamic tracking and precise landing of UAV based on visual magnetic guidance. Journal of ZheJiang University (Engineering Science), 2021, 55(1): 96-108.

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http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2021.01.012     OR     http://www.zjujournals.com/eng/Y2021/V55/I1/96


基于视觉-磁引导的无人机动态跟踪与精准着陆

针对无人机通过视觉对地面动态目标跟踪过程中视角固定易丢失目标，以及在着陆过程中由于成像畸变严重、画面不稳定导致定位精度差的问题，提出随动视觉跟踪的跟踪控制策略和基于视觉联合磁引导的获取无人机高精度相对位姿的方法. 在跟踪过程中，设计新型信标图案供无人机进行视觉识别获取目标的方位，识别速度可以达到5 ms/帧，通过随动视觉跟踪完成实时跟踪. 在着陆过程中，在动态目标上设置磁源，利用无人机检测磁场特性并通过BP神经网络解算相对位置；在信标图案内设置平行线特征，用于近镜头时辅助视觉解算相对角度. 在获取无人机相对位姿后，进行相应的运动控制即可完成着陆. 实验结果表明，跟踪过程稳定可靠，抗干扰能力强；着陆精度高，着陆误差小于2 cm.


关键词： 视觉跟踪,  视觉信标,  磁引导,  神经网络,  位姿解算 
Fig.1 Pose description of tracking process
Fig.2 Visual beacon and visual recognition results
Fig.3 Beacon pattern and beacon board installation diagram
Fig.4 Camera imaging plane
Fig.5 Imaging when camera is vertical
Fig.6 Imaging when camera tilts
Fig.7 Parallel hybrid PID controller
Fig.8 Ring electrified wire model
Fig.9 Physical and schematic diagram of I-shaped inductor
Fig.10 Sequence diagram of alternating current
Fig.11 Parallel resonance equivalent circuit diagram
Fig.12 Distribution of inductance and coil
Fig.13 Physical diagram of inductance and coil
Fig.14 Schematic diagram of UAV sensor layout
Fig.15 Voltage change at both ends of LC circuit
Fig.16 Data acquisition with help of manipulator
Fig.17 Coordinate points of UAV in turn
Fig.18 Signal intensity distribution of single inductor
Fig.19 Mean square error curve
Fig.20 Error histogram
Fig.21 Detection results of middle line of visual beacon
Fig.22 Schematic diagram of star window auxiliary analysis method
A A1 A2 A3 Q
${\rm{ - 9}}{{\rm{0}}^ \circ }$ ${\rm{ - 89}}{\rm{.9}}{{\rm{8}}^ \circ }$ ${\rm{ - 90}}{\rm{.3}}{{\rm{5}}^ \circ }$ ${\rm{ - 90}}{\rm{.2}}{{\rm{7}}^ \circ }$ ${\rm{ - 0} }{\rm{.2} }{ {\rm{5} }^ \circ },\;{0.02^ \circ }$
${\rm{ - 6}}{{\rm{0}}^ \circ }$ ${\rm{ - 60}}{\rm{.0}}{{\rm{4}}^ \circ }$ ${\rm{ - 40}}{\rm{.4}}{{\rm{6}}^ \circ }$ ${\rm{ - 59}}{\rm{.5}}{{\rm{3}}^ \circ }$ ${\rm{ - 0} }{\rm{.4} }{ {\rm{6} }^ \circ },\;{0.47^ \circ }$
${\rm{ - 3}}{{\rm{0}}^ \circ }$ ${\rm{ - 30}}{\rm{.3}}{{\rm{1}}^ \circ }$ ${\rm{ - 30}}{\rm{.3}}{{\rm{2}}^ \circ }$ ${\rm{ - 30}}{\rm{.3}}{{\rm{4}}^ \circ }$ ${\rm{ - 0} }{\rm{.3} }{ {\rm{4} }^ \circ },\;{0.31^ \circ }$
${{\rm{0}}^ \circ }$ ${\rm{ - 0}}{\rm{.0}}{{\rm{2}}^ \circ }$ ${\rm{ - 0}}{\rm{.4}}{{\rm{5}}^ \circ }$ ${\rm{0}}{\rm{.1}}{{\rm{1}}^ \circ }$ ${\rm{ - 0} }{\rm{.4} }{ {\rm{5} }^ \circ },\;{0.11^ \circ }$
${\rm{3}}{{\rm{0}}^ \circ }$ ${\rm{ - 29}}{\rm{.7}}{{\rm{4}}^ \circ }$ ${\rm{29}}{\rm{.6}}{{\rm{7}}^ \circ }$ ${\rm{29}}{\rm{.5}}{{\rm{4}}^ \circ }$ ${\rm{ - 0} }{\rm{.4} }{ {\rm{6} }^ \circ },\;{\rm{ - } }{0.26^ \circ }$
${\rm{6}}{{\rm{0}}^ \circ }$ ${\rm{60}}{\rm{.1}}{{\rm{2}}^ \circ }$ ${\rm{60}}{\rm{.0}}{{\rm{6}}^ \circ }$ ${\rm{59}}{\rm{.8}}{{\rm{8}}^ \circ }$ ${\rm{ - 0} }{\rm{.1} }{ {\rm{2} }^ \circ },\;{0.12^ \circ }$
${\rm{9}}{{\rm{0}}^ \circ }$ ${\rm{90}}{\rm{.2}}{{\rm{3}}^ \circ }$ ${\rm{90}}{\rm{.1}}{{\rm{7}}^ \circ }$ ${\rm{90}}{\rm{.0}}{{\rm{0}}^ \circ }$ ${ {\rm{0} }^ \circ },\;{0.23^ \circ }$
Tab.1 Test results of star window auxiliary analysis method
Fig.23 Physical picture of VAV and AGV experimental platform
Fig.24 Heading angle change of rectangular route following UAV
Fig.25 Follow up visual tracking
Fig.26 Conventional visual tracking
Fig.27 Beacon recognition results
Fig.28 Tracking process picture
Fig.29 Schematic diagram of landing process
Fig.30 Attitude change during landing under magnetic guidance
Fig.31 Attitude changes during landing under non magnetic guidance
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