During the replanting operation of a seedling tray, the end-effector needs to repeatedly grab the qualified plug seedlings in the supply tray and release them to the target tray for replanting, and in the process of grasping, the end-effector may cause some mechanical damage to the plug seedlings, thus affecting their quality. Therefore, in order to be able to adjust the position of the hand claw grasping point according to the morphological characteristics of the plug seedlings and select the optimal grasping point, this paper proposes research on the optimal grasping angle algorithm for plug seedlings based on machine vision. Firstly, a rotatable three-jaw end-effector is designed, which uses a three-jaw structure for grasping the burrowing seedlings. The three claws are driven with a telescopic cylinder to carry out clamping and relaxing actions. The rotation of the three claws is controlled with the stepper motor to adjust the optimal grasping position. Secondly, based on the pre-processing of an image of the hole tray seedling, the extraction of feature points in the region of interest, and the calculation of localization, the angle between the angular bisector of the cotyledon leaf blade of the hole tray seedling and the horizontal positive direction is solved. In this paper, two methods are designed to calculate the coordinates of feature points: one is the geometric method and the other is the center-of-mass method. Finally, the optimal grasping angle is calculated by analyzing the angle between the angular bisector of the cotyledon leaf blade and the horizontal positive direction of the cavity seedlings. According to the test, the average calculation error of the proposed algorithm is 3.12 degrees, and the average calculation time is 0.512 sec/sheet, which meet the requirements of the replanting operation.
