Intelligent Detection and Automatic Removal Robot for Skinned Garlic Cloves

Zhengbo Zhu, Xin Cao, Yawen Xiao (), Li Xin, Lei Xin and Shuqian Li
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Zhengbo Zhu: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China
Xin Cao: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China
Yawen Xiao: School of Mechanical Engineering, Yangzhou University, Yangzhou 225000, China
Li Xin: Shandong Maria Machinery Co., Ltd., Jinxiang 272299, China
Lei Xin: Shandong Maria Machinery Co., Ltd., Jinxiang 272299, China
Shuqian Li: Shandong Maria Machinery Co., Ltd., Jinxiang 272299, China

Agriculture, 2025, vol. 15, issue 10, 1-15

Abstract: After undergoing peeling-machine operations, skinned garlic cloves affect subsequent processing, and their manual removal is harmful to health. In this paper, an intelligent garlic-clove-removal test bench was designed, which mainly included a hopper, lifter, vibration conveyor, conveyor belt, visual system, removal robot, control cabinet, frame, etc. A technical method based on machine vision technology to distinguish whether or not garlic cloves had a skin was explored to ensure that the test bench could complete the recognition of the skinned garlic cloves, and to check that the test bench could also complete the removal of skinned garlic cloves. Tests were carried out to check the success rate of machine vision and the removal robot, and to optimize the parameters of the test bench. The results showed that the average success rate of machine vision was 99.15%, and the average success rate of the removal robot was 99.13%. The results also showed that the order of the three factors influence index was the conveying speed, the conveying volume, and the removal period. The regression analysis showed that when the conveying speed was 0.1 m·s −1 , the grasping period was 1.725 s, the conveying volume was 104.4 kg·h −1 , the qualified rate of the finished product was 97.15%, and the verification test result was 97.02%, which had no significant difference from the analysis result. The research results of this paper are conducive to the development of intelligent detection technology of garlic cloves, and to the development of garlic-planting technology and deep processing technology.

Keywords: intelligent detection; robot; machine vision; parameter optimization; garlic clove; removal rate (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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