Potential analysis of an automatic transplanting method for healthy potted seedlings using computer vision

Abstract

Healthy seedlings transplanting is an important process in the production of vegetables and economic crops, and the transplanting quality directly affects crop yield. Automatic seedlings transplanting can improve the transplanting efficiency of seedlings. A physical prototype of potted seedling automatic transplanting with a conveyor and a transplanting end-effector was developed in the previous study. This work proposed an automatic transplanting method of healthy potted seedlings, which mainly included a detection part of seedlings growth status and a visual servo control part with the purpose of automatic transplanting seedlings high-efficiently. The seedlings and the tray cell were simultaneously detected for identifying healthy seedlings, damaged seedlings and empty cells using a machine vision algorithm when the tray was moving on the conveyor line. The visual servo model was applied to enable the collaborative operation of the machine vision and the end-effector for determining the position and attitude of grasping seedlings. The experimental results showed that the accuracy rates of the identification of empty tray cells, healthy seedling and unhealthy seedling were 96.42%, 98.77% and 89.95%, respectively. Under the successful identification of the healthy seedling, the accuracy rate of grasping seedling was 96.38%. It indicated that the proposed method can effectively transplant seedlings.