王东,范叶满,薛金儒,袁端,沈楷程,张海辉.基于GNSS与视觉融合的山地果园无人机航迹控制[J].农业机械学报,2019,50(4):20-28.
WANG Dong,FAN Yeman,XUE Jinru,YUAN Duan,SHEN Kaicheng,ZHANG Haihui.Flight Path Control of UAV in Mountain Orchards Based on Fusion of GNSS and Machine Vision[J].Transactions of the Chinese Society for Agricultural Machinery,2019,50(4):20-28.
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基于GNSS与视觉融合的山地果园无人机航迹控制   [下载全文]
Flight Path Control of UAV in Mountain Orchards Based on Fusion of GNSS and Machine Vision   [Download Pdf][in English]
投稿时间:2019-01-20  
DOI:10.6041/j.issn.1000-1298.2019.04.002
中文关键词:  山地果园  航空植保  无人机  航迹控制  机器视觉  GNSS导航
基金项目:国家自然科学基金项目(31701326)和国家重点研发计划项目(2018YFD0701102)
作者单位
王东 西北农林科技大学 
范叶满 西北农林科技大学 
薛金儒 西北农林科技大学 
袁端 西北农林科技大学 
沈楷程 西北农林科技大学 
张海辉 西北农林科技大学 
中文摘要:为精准控制无人机航迹稳定、准确进行山地果园的航空植保作业,以四旋翼无人机为载体,设计了基于GNSS与视觉导航融合的山地果园无人机植保航迹控制系统。该系统由无人机飞行平台和地面控制站两部分组成。其中,无人机平台由四旋翼无人机、内环飞控、GNSS移动站、RGB相机、无线视频发射模块和电子罗盘组成;控制站由GNSS基站、飞行控制模块、便携式计算机、无线视频接收模块和视频采集模块组成。基于Python语言,结合OpenCV库,设计了果树行识别算法。采用线性组合算法提取目标行作业区域,利用最小二乘法对作业区域中心点进行拟合,得到果树行趋势线,进而计算出偏航角,以实现无人机作业航迹控制。山地苹果园的导航控制试验结果表明,当无人机飞行速度为2m/s,距离果树冠层高度约2m,相机倾角为46°,视觉导航控制率为2次/s时,该系统航迹控制误差范围为-47~42cm,平均误差为-9cm,系统控制精度较高,可满足无人机对山地果园植保作业的要求。
WANG Dong  FAN Yeman  XUE Jinru  YUAN Duan  SHEN Kaicheng  ZHANG Haihui
Northwest A&F University,Northwest A&F University,Northwest A&F University,Northwest A&F University,Northwest A&F University and Northwest A&F University
Key Words:mountain orchard  aviation plant protection  unmanned aerial vehicle  flight path control  machine vision  GNSS navigation
Abstract:Precise path control of unmanned aerial vehicle (UAV) is the key technology to realize aviation plant protection in mountain orchards. In order to carry out the plant protection operation stably and accurately in mountain orchards, based on the four-rotor UAV, the flight path control system and method of UAV for plant protection by fusing GNSS and machine vision were designed. The system consisted of two parts, i.e., UAV flight platform and ground control station. The former consisted of a four-rotor UAV, an inner-ring flight control module, a GNSS moving station, a RGB camera, a wireless video transmission module and an electronic compass. The latter consisted of a GNSS base station, a flight control module, a laptop and a video capture module. A fruit tree row recognition algorithm was proposed based on Python language combined with OpenCV library. In this algorithm, a linear combinatorial algorithm was used to extract the target area, and the least squares method was used to fit the central point of target area to obtain the row trend of fruit tree. Then the yaw angle was calculated to realize the path control. In the working process, the UAV was controlled by the visual navigation method when flying over the fruit tree, while controlled by the GNSS navigation method when it needed to switch between rows of different operation fruit trees. The developed system and proposed method was tested in mountain apple orchard. The results showed that when the flight speed was 2m/s, the height of UAV from fruit tree canopy was about 2m, the camera’s dip angle was 46° and the image navigation control rate was 2 times/s, the absolute path control error of the system was -47~42cm, and the average absolute error was -9cm. The high control precision indicated that the system could meet the requirements of UAV for plant protection operation in mountain orchards. The research provided a new method for path control of UAV on plant protection in mountain orchards.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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