Vision-Based Smart Sprayer for Precision Farming

被引:0
|
作者
Deguchi, Thaidy [1 ,2 ]
Baltazar, Andre Rodrigues [2 ]
dos Santos, Filipe Neves [2 ]
Mendonca, Helio [1 ,2 ]
机构
[1] Univ Porto, FEUP Fac Engn, P-4200465 Porto, Portugal
[2] INESC TEC Inst Syst & Comp Engn Technol & Sci, CRIIS Ctr Robot Ind & Intelligent Syst, P-4200465 Porto, Portugal
关键词
precision farming; machine learning; computer vision; robotics; GRAPEVINES;
D O I
10.1007/978-3-031-59167-9_27
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Since the advent of agriculture, humans have considered phytopharmaceutical products to control pests and reduce losses in farming. Sometimes some of these products, such pesticides, can potentially harm the soil life. In the literature there is evidence that AI and image processing can have a positive contribution to reduce phytopharmaceutical losses, when used in variable rate sprayers. However, it is possible to improve the existing sprayer system's precision, accuracy, and mechanical aspects. This work proposes spraying solution called GraDeS solution (Grape Detection Sprayer). GraDeS solution is a sprayer with two degrees of freedom, controlled by a AI-based algorithm to precisely treat grape bunches diseases. The experiments with the designed sprayer showed two key points. First, the deep learning algorithm recognized and tracked grape bunches. Even with structure movement and bunch covering, the algorithm employs several strategies to keep track of the discovered objects. Second, the robotic sprayer can improve precision in specified areas, such as exclusively spraying grape bunches. Because of the structure's reduced size, the system can be used in medium and small robots.
引用
收藏
页码:324 / 335
页数:12
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