• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1998.12a
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• pp.216-222
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• 1998

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1998.12a
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• pp.475-480
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• 1998

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1998.12a
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• pp.481-486
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• 1998

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.698-706
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• 2000

It is very difficult to mechanize tomato harvesting because identifying a tomato partly covered with leaves and stalks is not easy. This research was conducted to develop tomato harvesting robot which can identify a target tomato, determine its three dimensional position, and harvest it in a limited time. Followings were major findings in this study. The first visual system of the harvesting robot was composed of two CCD cameras, however, this could not detect tomatoes which are not seen on the view finder of the camera especially those partly covered by leaves or stalks. The second visual device, combined with two CCD cameras and pan/tilt procedures was designed to minimize the positioning errors within ${\pm}10mm$, but this is still not enough to detect tomatoes partly covered with leaves etc. Finally, laser distance detector was added to the visual system that could reduce the position detecting errors within 10mm in X-Y direction and 5mm in Z direction for the partly covered tomatoes.

• KIISE Transactions on Computing Practices
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• v.21 no.11
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• pp.689-698
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• 2015

Currently, the itemized box loading operation at the Agriculture Products Processing Center which distributes agricultural products for the region is carried out manually. The process of loading agricultural products requires great manpower and had been resolved through the part-time employment of the residents of farm villages. However, recently it has become quite difficult to secure manpower as the aging within the rural community has been intensified. Hence, the necessity for countermeasures such as facility automation or use of robots have become necessary. This study suggests an automatic robot system for the itemized loading of apple boxes at the Agriculture Products Processing Center. The suggested method is to design and develop equipment such as a conveyer, robot, and bar code reader. In addition, a sorting plan, operational control, generation of control information, and software module that could monitor the inside of the Agriculture Products Processing Center is needed. After test-operating and evaluating the developed system, the existing manual work would be replaced with the automated robot system in order to enhance work efficiency and resolve safety issues.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.354-362
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• 2000

In Korea, researches on year-round leaf vegetables production system are in progress, most of them focused on environmental control. Therefore, automation technologies for harvesting, transporting, and grading are in great demand. A robot system for harvesting lettuces, composed of a 3-DOF (degree of freedom) manipulator, an end-effector, a lettuce feeding conveyor, an air blower, a machine vision system, six photoelectric sensors, and a fuzzy logic controller, was developed. A fuzzy logic control was applied to determine appropriate grip force on lettuce. Leaf area index and height were used as input variables and voltage as an output variable for the fuzzy logic controller. Success rate of the lettuce harvesting was 94.12%, and average harvesting time was approximately 5 seconds per lettuce.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.313-317
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• 2000

In this research, a grafting robot with plug in method is used. Plug in method is a method that uses a tapered axis for scion and a tapered hole for stock as processing style of conjugation parts. In the case of handling a grafting seedling, gripping a stem is doing with simple mechanisms of devising to reduce damages to stems. For example, providing cushions between gripper and stem, and fitting a gripper to a stem. Both scions and stocks need cutting, but there is bigger influence for scions than stocks, so problems of cutting scions and special qualities of grippers are necessary to investigate.

• Journal of Biosystems Engineering
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• v.30 no.5 s.112
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• pp.293-298
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• 2005

The purpose of this study was the development of a multi-joint robot manipulator for milking robot system. The multi-joint robot manipulator was controlled by 5 drivers with driver controller through the position information obtained from the image processing system. The robot manipulator to automatically attach each teat cup to the teats of a milking cow was developed and it's motion was accurately measured with error rate. Results were as follows. 1. Maximum errors in position accuracy were 4mm along X-axis, 4.5mm along Y-axis and 0.9mm along Z-axis. Absolute distance errors were maximum 4.8mm, minimum 2.7mm, and average 3.6mm. 2. Errors of repeatability were maximum 3.0mm along X-axis, 3.0mm along Y-axis, and 0.5mm along Z-axis. Distance error values were maximum 3.2mm, minimum 2.2mm, and average 2.5mm. It is envisaged that multi-joint robot manipulator can be applicate to milking robot system being developed in consideration of the experiment results.

• Electronics and Telecommunications Trends
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• v.36 no.2
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• pp.22-31
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• 2021

This report introduces a definition for robot task intelligence and explains the basis of the challenges associated with implementing robot task intelligence in real-world problems. Two fundamental elements of this intelligence, robot manipulation and navigation, are introduced herein. We describe the existing trends and industrial applications of the robot task intelligence in logistics and agricultural automation. Furthermore, as an underpinning technology for this intelligence, we review the existing three-dimensional position estimation techniques and summarize the difficulties associated with applying pure SLAM technology to real-world applications. Finally, we discuss the prospects of the robot task intelligence research and its potential for solving real-world problems.

• The Journal of Korea Robotics Society
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• v.11 no.1
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• pp.1-8
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• 2016

In this paper, we propose a new algorithm of the guidance line extraction for autonomous agricultural robot based on vision camera in paddy field. It is the important process for guidance line extraction which finds the central point or area of rice row. We are trying to use the central region data of crop that the direction of rice leaves have convergence to central area of rice row in order to improve accuracy of the guidance line. The guidance line is extracted from the intersection points of extended virtual lines using the modified robust regression. The extended virtual lines are represented as the extended line from each segmented straight line created on the edges of the rice plants in the image using the Hough transform. We also have verified an accuracy of the proposed algorithm by experiments in the real wet paddy.