| Project/Area Number |
11660252
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
農業機械学
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| Research Institution | Iwate University |
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Principal Investigator |
TAKEDA Jun-ichi Iwate Univ., Faculty of Agriculture, Associate Professor, 農学部, 助教授 (80133908)
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| Co-Investigator(Kenkyū-buntansha) |
KATAOKA Takasi Iwate Univ., Former Faculty of Agriculture, Research Associate, 農学部, 助手 (40231253)
IMAE Jyo Iwate Univ., Former Faculty of Engineering, Associate Professor, 工学部, 助教授 (30184807)
TORISU Ryo Iwate Univ., Faculty of Agriculture, Professor, 農学部, 教授 (70038264)
MAEDA Takeki Iwate Univ., Faculty of Agriculture, Research Associate, 農学部, 助手 (40333760)
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| Project Period (FY) |
1999 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2001: ¥400,000 (Direct Cost: ¥400,000)
Fiscal Year 2000: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 1999: ¥2,600,000 (Direct Cost: ¥2,600,000)
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| Keywords | Levee / Weeding / Autonomous Vehicle / Image Processing / HSI Transform / Hough Transform / 自律走行 / GPS |
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| Research Abstract |
Most of the works for rice farming is now carried out by riding type agricultural machines such as tractors, rice planting machines, rice combines and so on. The levee weeding in rice farming is one of the remaining severe work in Japan. The purpose of this research work is carried out to develop levee weeding robot that works autonomously.
The results of this research work are summarized as follows :
1) The crawler type vehicle was selected for main body of the weeding robot. The near infrared beam type sensors are installed on the side of the vehicle to detect the shape of the levee and fiber optical gyroscope sensor was also installed to detect vehicle heading angle. The mower was installed in front of the vehicle.
2) The navigation strategy was proposed. The turning angle of the vehicle was decided by using the deviation between the virtual focusing point in front of the vehide and referenced line that is the center line of the levee. The vehicle can be run to use turning and strait running repeatedly. The simulated and experimental results are almost the same by proving the proposed strategy.
3) The machine vision analysis was applied to detect the edge of the levee. The image was taken from degital video camera and treated to filtering, then HSI transform was made to have binary image and linear regression line or Hough transform was made to detect the levee line. Hough transform was very effective to detect the levee line from complicated images even if there are a few strait points on the binary images.
The GPS was effective for detecting the vehicle position except to use near tall trees surrounding the paddy field. The autonomous mowing procedure could not be in the process because of the delay of adjustment about the clutch. Then the project will be continuously carried out to find out the adaptability of the robot on the levee weeding.
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