Open AccessTomato Recognition for Harvesting Robots Considering Overlapping Leaves and Stems
Author(s) -
Takeshi Ikeda,
Ryo Fukuzaki,
Masanori Sato,
Seiji Furuno,
Fusaomi Nagata,
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Publication year - 2021
Publication title -
journal of robotics and mechatronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.257
H-Index - 19
eISSN - 1883-8049
pISSN - 0915-3942
DOI - 10.20965/jrm.2021.p1274
Subject(s) - robot , robotics , image processing , artificial intelligence , agricultural engineering , realization (probability) , computer science , agriculture , population , robotic arm , computer vision , image (mathematics) , engineering , mathematics , geography , statistics , demography , archaeology , sociology
In recent years, the declining and aging population of farmers has become a serious problem. Smart agriculture has been promoted to solve these problems. It is a type of agriculture that utilizes robotics, and information and communication technology to promote labor saving, precision, and realization of high-quality production. In this research, we focused on robots that can harvest tomatoes. Tomatoes are delicate vegetables with a thin skin and a relatively large yield. During automatic harvesting of tomatoes, to ensure the operation of the harvesting arm, an input by image processing is crucial to determine the color of the tomatoes at the time of harvesting. Research on robot image processing technology is indispensable for accurate operation of the arm. In an environment where tomatoes are harvested, obstacles such as leaves, stems, and unripe tomatoes should be taken into consideration. Therefore, in this research, we propose a method of image processing to provide an appropriate route for the arm to ensure easy harvesting, considering the surrounding obstacles.