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浙江大学学报(工学版)
Journal of ZheJiang University (Engineering Science)  2019, Vol. 53 Issue (5): 880-888    DOI: 10.3785/j.issn.1008-973X.2019.05.008
    
Vision-based localization and navigation for UAV inspection in photovoltaic farms
Zhi-peng XI(),Zhuo LOU,Xiao-xia LI,Yan SUN,Qiang YANG*(),Wen-jun YAN
College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
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Abstract  

In order to achieve autonomous flight for unmanned aerial vehicles (UAVs) in PV farms and complete infrared and visible-light image acquisition, an edge detecting method for photovoltaic (PV) strings was proposed and the line of sight guidance based path following control algorithm was carried out according to the distribution characteristics of PV strings. Color variance widely existes among different PV modules in the same PV farm, based on which a custom color segmentation technique was put forward. This technique could be combined with shape features to realize accurate identification for PV modules. Theoretical flight paths could be gained through contour and edge information of PV strings after which the line of sight guidance method was applied to accurate trajectory tracking control for theoretical path to guarantee the effectiveness and integrity of image data acquisition. Results showed that the proposed recognition algorithm for PV strings was excellent in adaptability and instantaneity and could be used to calculate the theoretical flight direction of UAV and the offsets between the UAV and PV strings, and the ideal trajectory tracking for PV strings can be realized through the navigation control algorithm. The identification approach for PV strings and the line of sight guidance method can work well in localization and navigation respectively, and combination of the two procedures can meet the requirements of UAV flight control.

Key words： photovoltaic inspection      quad-rotor unmanned aerial vehicle (UAV)      vision localization      path following      autonomous flight     
Received: 26 June 2018      Published: 17 May 2019
CLC:  TP 29  
Corresponding Authors: Qiang YANG     E-mail: xizhipeng@zju.edu.cn;qyang@zju.edu.cn
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Zhi-peng XI
Zhuo LOU
Xiao-xia LI
Yan SUN
Qiang YANG
Wen-jun YAN
Cite this article:

Zhi-peng XI,Zhuo LOU,Xiao-xia LI,Yan SUN,Qiang YANG,Wen-jun YAN. Vision-based localization and navigation for UAV inspection in photovoltaic farms. Journal of ZheJiang University (Engineering Science), 2019, 53(5): 880-888.

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http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2019.05.008     OR     http://www.zjujournals.com/eng/Y2019/V53/I5/880


集中式光伏电站巡检无人机视觉定位与导航

为了使无人机在集中式光伏电站实现自主飞行，完成光伏组件红外及可见光图像采集任务，针对集中式光伏厂区光伏组串分布特点，提出光伏组串边缘检测方法，并通过视线导引法实现无人机路径跟随控制. 同一厂区的不同光伏组件之间存在颜色差异，针对其颜色特征提出自定义分割方法，结合形状特征可有效识别光伏组件；提取光伏组串轮廓和边缘信息可获取无人机理论飞行路径，通过视线导引法实现无人机对理论飞行路径的精准跟随以确保图像数据采集的有效性和完整性. 实验结果表明，提出的光伏组串识别算法具有较好的适应性和实时性，能够用于无人机理论飞行方向与无人机和光伏组串间偏移量的计算，利用导航控制算法能够实现理想的光伏组串循迹. 光伏组串识别算法和视线导引法能分别有效实现定位和导航，2个程序的结合能够满足无人机飞行控制要求.


关键词： 光伏巡检,  四旋翼无人机(UAV),  视觉定位,  路径跟随,  自主飞行 
Fig.1 Sketch map of region division in a centralized PV farm
Fig.2 Flowchart of UAV navigation method
Fig.3 Typical color features of PV modules
Fig.4 Histogram distribution of four PV modules in RGB color space
Fig.5 Color feature histogram of PV modules in custom rules
Fig.6 Identification process for PV strings
Fig.7 Contour of PV string
Fig.8 Edge line detection result of PV string
Fig.9 Angle relationship in NED coordinate
Fig.10 Schematic diagram of UAV path following process
Fig.11 Schematic diagram of flight velocity of UAV
Fig.12 Schematic diagram of turning procedure of UAV
Fig.13 Identification results for PV modules and edge detection effect for PV strings under different scenarios
特征时间 T/ms
颜色特征提取时间 20
形状特征提取时间 15
组串定位时间 4
边缘直线检测时间 12
总时间 51
Tab.1 Real time analysis of image processing algorithm
Fig.14 Simulation results of navigation and control process of UAV based on line of sight guidance algorithm
Fig.15 Overhead view of distribution of PV modules and flight path of UAV
Fig.16 Variation trend of offsets between UAV and PV modules
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