Development of an Automatic Grafting Robot for Fruit Vegetables using Image Recognition

Abstract

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 2.50.3mm and 2.20.2mm for scions and 3.10.7mm and 3.60.3mm 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 963.2% and 954%, respectively.