Abstract
In manually propagating potato test-tube plantlets (PTTPs), the plantlet is usually grasped and cut at the node point between the cotyledon and stem, which is hardly located and is easily damaged by the gripper. Using an agricultural intelligent robot to replace manual operation will greatly improve the efficiency and quality of the propagation of PTTPs. An automatic machine vision-guided system for the propagation of PTTPs was developed and tested. In this paper, the workflow of the visual system was designed and the image acquisition device was made. Furthermore, the image processing algorithm was then integrated with the image acquisition device in order to construct an automatic PTTP propagation vision system. An image processing system for locating a node point was employed to determine a suitable operation point on the stem. A binocular stereo vision algorithm was applied to compute the 3D coordinates of node points. Finally, the kinematics equation of the three-axis parallel manipulator was established, and the three-dimensional coordinates of the nodes were transformed into the corresponding parameters X, Y, and Z of the three driving sliders of the manipulator. The experimental results indicated that the automatic vision system had a success rate of 98.4%, 0.68 s time consumed per 3 plants, and approximate 1 mm location error in locating the plantlets in an appropriate position for the medial expansion period (22 days).
Highlights
Potato is one of the most important crops around the world
The technology of the propagation of virus-free potato test-tube plantlets has solved the problem of yield and quality degradation caused by a virus infection, which increases potato yield by more than 30%. e propagation of virus-free tube potato plantlets is the basic link of the yield of the potato virus-free seed potato breeding system
To mimic the manual transplantation operation, this study developed an image processing algorithm based on a binocular stereo vision system to segment the Phalaenopsis tissue culture plantlets (PTCPs) image into its constituent leaf and root components and to locate a suitable grasping position on the PTCP body. e locating algorithm was integrated with a robotic gripper in order to construct an automatic Phalaenopsis plantlet grasping system [14]
Summary
Potato is one of the most important crops around the world. Nowadays, the technology of the propagation of virus-free potato test-tube plantlets has solved the problem of yield and quality degradation caused by a virus infection, which increases potato yield by more than 30%. e propagation of virus-free tube potato plantlets is the basic link of the yield of the potato virus-free seed potato breeding system. E system uses the embedded machine vision technology to identify and locate the plantlets nodes and get, cut, and transplant the plantlets with a self-developed 5-DOF joint robot arm. Zhang et al proposed a vision system used in the plantlet transplanting of cucurbit taking into consideration the actual working conditions of the self-made robot system In this system, the information of the cross-sectional diameter size could quickly be extracted from the color image of the crop plantlets and automatically detect the spatial location of growth points [19]. Combined with the actual working conditions of a selfmade parallel robot system, this paper focuses mainly on locating the spatial coordinates of the cutting points on a stem of the test-tube plantlet for the end effector and presents a method for acquiring spatial information from the test-tube plantlet based on binocular stereo vision.
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