Development of a positioning system using UAV-based computer vision for an airboat navigation in paddy field

被引:24
作者
Liu, Yufei [1 ,2 ]
Noguchi, Noboru [2 ]
Liang, Lingguang [3 ]
机构
[1] Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou, Zhejiang, Peoples R China
[2] Hokkaido Univ, Res Fac Agr, Kita8,Nishi5, Sapporo, Hokkaido 0608589, Japan
[3] Hokkaido Univ, Grad Sch Agr, Sapporo, Hokkaido, Japan
关键词
Agricultural airboat; Autonomous navigation; Computer vision; Positioning system; UAV; UNMANNED AERIAL VEHICLE; PLATFORM;
D O I
10.1016/j.compag.2019.04.009
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Currently, a few agricultural corporations are developing and producing a kind of radio-controlled agricultural airboat which could be used to weed and fertilize instead of human in the paddy fields. The authors improved the airboat realizing autonomous navigation by a global-positioning-system (GPS) compass in the previous research. To solve the limitation of GPS-based navigation in bad environment (e.g., areas with tall trees, bad weather conditions, etc.), a new positioning system was proposed by using a computer vision system mounted on an unmanned aerial vehicle (UAV) to provide position information for an agricultural airboat engaged in autonomous fertilizing and herbicide application in this study. The computer vision system included a minicomputer, a color camera with a wide-angle lens, and a Bluetooth transmitter. The UAV was operated to hover high enough to overlook the paddy field by the computer vision system. The colored concentric circular markers were made to put at the corners of the paddy field to facilitate the paddy field recognition using Fitzgibbon ellipse fitting algorithm. Utilize the geographic position by GPS and image position by computer vision system of each markers to obtain the perspective transformation matrix for transforming the top view image of the paddy field. At the created paddy-field-based coordinate, the UAV detects the airboat position by using the white color feature and central symmetrical contour feature of the airboat and transmits the position information to airboat in real time by Bluetooth for airboat navigation. The results of navigation experiment showed that the RMS lateral errors were 0.17 m, 0.10 m and 0.11 m in 3 predefined paths, respectively. This accuracy level was better than that of differential-GPS (DGPS). It is acceptable for providing positioning service for the airboat autonomous navigation in paddy fields. Furthermore, this UAV-airboat solution was a beneficial attempt which can not only prevent the instability of GPS-based airboat navigation in bad environment, but also avoid the herbicide spray drift problem that occurs in UAV-spraying in the air.
引用
收藏
页码:126 / 133
页数:8
相关论文
共 25 条
[1]  
[Anonymous], 2008, LEARNING OPENCV COMP
[3]  
Brouwer C., 1989, TRAINING MANUAL
[4]   Forest fire monitoring with multiple small UAVs [J].
Casbeer, DW ;
Beard, RW ;
McLain, TW ;
Li, SM ;
Mehra, RK .
ACC: Proceedings of the 2005 American Control Conference, Vols 1-7, 2005, :3530-3535
[5]   Color image segmentation: advances and prospects [J].
Cheng, HD ;
Jiang, XH ;
Sun, Y ;
Wang, JL .
PATTERN RECOGNITION, 2001, 34 (12) :2259-2281
[6]  
Fiorillo F, 2013, VIRTUAL ARCHAEOL REV, V4, P55
[7]   Direct least square fitting of ellipses [J].
Fitzgibbon, A ;
Pilu, M ;
Fisher, RB .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1999, 21 (05) :476-480
[8]  
Franklin P. K, 2007, SPRAY DRIFT AERIAL A
[9]   Deployment and Performance of a UAV for Crop Spraying [J].
Giles, Durham K. ;
Billing, Ryan C. .
FRUTIC ITALY 2015: 9TH NUT AND VEGETABLE PRODUCTION ENGINEERING SYMPOSIUM, 2015, 44 :307-312
[10]  
Hirafuji M, 2004, P WORLD RIC RES C, P568