• Journal of Biosystems Engineering
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• v.29 no.3
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• pp.281-286
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• 2004

The end-effector is the one of the important factors on development of the cucumber robot to harvester a cucumber. Three end-effectors were designed the single blade end-effector with one blade, the double blade end-effector with two blades and the triple blade end-effector with three blades. Performance tests of the end-effector, the fully integrated system, were conducted to determine the cutting rate by using two different kinds of cucumber. The success rates of cucumber cutting ratio of single end-effector, double end-effector and triple end-effector in laboratory. were 61.7%, 95%, 86.7%, respectively. The cutting rate of single blade or double blade was a little difference with respect to the different diameters of cucumber stem. However, the success cutting rate of the end-effector with triple blade was 61.7% under 29mm diameter of a grabbing stem section. The triple end-effector was not suitable for harvesting a cucumber, but was considered to be suitable for harvesting a grape, an apple and a tomato. The success rate of cucumber cutting ratio of triple end-effectors in greenhouse was 84%. The failure cutting rate was 16% which are due to abnormal shape of cucumber fruit.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.859-866
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• 1993

With the object of doing mechanical grafting of cucurbitaceous vegetables, the grafting robot was developed in 1989. This robot consists of the following components : feeding wheels, grippers, conveying wheels, cutters , fixing clipper, discharger , controller and power supply. One cycle time to produce a grafted plant is about 3 seconds, Results of some cucumber grafting tests : successful grafting rate of 98 percent and after acclimation, a successful agglutination rate of 95 percent. These techniques are now transferring to the private company. The commercial robot will come into the market in this year.

• Journal of Biosystems Engineering
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• v.33 no.6
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• pp.453-461
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• 2008

This study was conducted to develop a root-removed splice grafting system for cucurbitaceous vegetables, mainly watermelon and cucumber seedlings, for the seedlings factories where currently most of seedlings grafting works are carried out by manual works. The major results of the study are as follows. The dimensions of rootstocks and scions, except cotyledon width, of root- removed splice grafting of watermelon and cucumber were shown to be varied within the 2.5-fold range. The growth status of seedlings were not consistent in terms of cotyledon sprouting direction and angle which were considered as one of the important factors for in root-removed splice grafting. The grafting work of root-removed splice for grafted watermelon and cucumber could be divided by four sub-operations: seedling supplying, cutting, clipping and potting, while a part or all root of the rootstock was removed in the seedlings supplying operation. The cutting angles of the rootstock and scion were $34-45^{\circ}$ and $20-45^{\circ}$, respectively, while the stem length of the scion varied from 6 mm to 12 mm. The splices of rootstock and scion were heaped up in parallel and then fixed by a clip. It indicated that the ideal grafting system, adopting conventional grafting processes of seedlings specifications as well as conventionally manual root-removed splice grafting method, performed very well for seedlings gripping and transporting, supplying clip, clipping and discharging grafted seedlings while workers supplied seedlings to the semi-automatical system.

• Journal of Bio-Environment Control
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• v.20 no.2
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• pp.63-71
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• 2011

Pattern recognition of a cucumber were conducted to detect directly the binary images by using thresholding method, which have the threshold level at the optimum intensity value. By restricting conditions of learning pattern, output patterns could be extracted from the same and similar input patterns by the algorithm. The algorithm of pattern recognition was developed to determine the position of the cucumber from a real image within working condition. The algorithm, designed and developed for this project, learned two, three or four learning pattern, and each learning pattern applied it to twenty sample patterns. The restored success rate of output pattern to sample pattern form two, three or four learning pattern was 65.0%, 45.0%, 12.5% respectively. The more number of learning pattern had, the more number of different out pattern detected when it was conversed. Detection of feature pattern of cucumber was processed by using auto scanning with real image of 30 by 30 pixel. The computing times required to execute the processing time of cucumber recognition took 0.5 to 1 second. Also, five real images tested, false pattern to the learning pattern is found that it has an elimination rate which is range from 96 to 98%. Some output patterns was recognized as a cucumber by the algorithm with the conditions. the rate of false recognition was range from 0.1 to 4.2%.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.322-327
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• 2019

This study was conducted to improve the performance of automatic grafting robot using image recognition technique. The stem diameters of tomatoes and cucumber at the time of grafting were $2.5{\pm}0.3mm$ and $2.2{\pm}0.2mm$ for scions and $3.1{\pm}0.7mm$ and $3.6{\pm}0.3mm$ for rootstocks, respectively. The grafting failure was occurred when the different height between scions and rootstocks were over 4 mm and below 2 mm due to the small contact area of both cutting surface. Therefore, it was found that the height difference at the cutting surface of 3 mm is appropriate. This study also found that grafting failure was occurred when the stem diameters of both scions and rootstocks were thin. Therefore, it was suggested to use at least one stem with thicker than the average stem diameter. Field survey on the cutting angle of stems by hand were ranged from 13 to 55 degree for scions and 15 to 67 degree for rootstocks, respectively, which indicates that this could cause the grafting failure problem. However, the automatic grafting robot developed in this study rotates the seedlings 90 degree and then the stems are cut using a cutting blade. The control part of robot use all images taken from grafting process to determine the distance between a center of both ends of stem and a gripper center and then control the rotation angle of a gripper. Overall, this study found that The performance of automatic grafting robot using image recognition technique was superior with the grafting success rates of cucumber and tomato as $96{\pm}3.2%$ and $95{\pm}4%$, respectively.

• Journal of Bio-Environment Control
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• v.13 no.1
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• pp.1-7
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• 2004

This study is kinematics for the manipulator development of cucumber harvesting. A theory value was verified by repeated error measurement after the forward kinematics or inverse kinematics analysis of manipulator. Manipulator is consisted of one perpendicular link and two revolution link. The transformation of manipulator can be valued by kinematics using Denavit-Hartenberg parameter. The value of inverse kinematics which is solved by three angles faction shows two types. Repeated errors refered maximum 2.60 mm, 2.05mm and 1.55 mm according to X, Y, Z axis. In this study, the actual coordinates of maximum point and minimum point were agreement in the forward kinematics or inverse kinematics. The results of repeated error measurement were reflect to be smaller compared to a diameter of cucumber. measurement errors were determined by experimented errors during the test. For reducing errors of manipulator and improving work efficiency, the number of link should be reduced and breeding and cultural environment should be considered to reduce the weight and use the hard stuff. The velocity of motor for working should be considered, too.