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

作　　者：Xin Jin Lumei Tang Jiangtao Ji Chenglin Wang Shengsheng Wang 

机构地区：[1]College of Agricultural Equipment Engineering,Henan University of Science and Technology,Luoyang 471003,China [2]School of Intelligent Manufacturing Engineering,Chongqing University of Arts and Sciences,Yongchuan,Chongqing 402160,China [3]Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing of Henan Province,Luoyang 471003,China

出　　处：《International Journal of Agricultural and Biological Engineering》2021年第6期162-168,共7页国际农业与生物工程学报（英文）

基　　金：supported by the National Natural Science Foundation of China(Grant No.51875175);the National Science Foundation of Henan(Grant No.202300410124);Intelligent Manufacturing Comprehensive Standardization Project(Grant No.2018GXZ1101011);Yongchuan Natural Science Foundation Project(Grant No.Ycstc,2019nb0802).

摘　　要：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.We developed a physical prototype of potted seedling automatic transplanting with a conveyor and a transplanting end-effector 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 implied that our proposed method can effectively transplant seedlings.

关 键 词：seedling recognition automatic transplanting computer vision transplanting system 

分 类 号：S51[农业科学—作物学]