Roundness measurement of cigarette based on visual information

Cao, Junli; Li, Ju-Feng; Lu, Teng-Da

doi:10.1007/s40436-017-0176-7

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…This system uses the MatchTemplate function of image processing library OpenCV to experiment and selects the normalized square difference matching method to find the target position. The matching formula is in equation (6).…”

Section: Terminal Head Alignmentmentioning

confidence: 99%

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Automatic buckling system of micro terminals combined vision and force signals

Jiang

Zhang

et al. 2023

Measurement and Control

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Micro terminals are often used in every laptop, mobile, and other electrical product. It is challenging to automatically buckle the terminal head to its terminal base during manufacturing because of trouble in accurate positioning and gripping. A double-robots collaborative assembly system is developed to buckle millimeter-scale terminals in three-dimensional space. Robot 1 takes the terminal head horizontally by grasping its flexible line with a customized clamp, including two fingers. Robot 2 presses the aligned terminal head through a force control strategy to ensure that the terminal head and the terminal base can complete buckling accurately, even if there is a certain deviation in the vertical direction. There are two cameras to be used in the system. A horizontally placed camera is used to detect and calculate the angle between the terminal head and the horizontal plane. The angle data will drive robot 1 to make the terminal end face parallel to the horizontal plane to complete the pose correction of the terminal head. Another camera is vertically fixed at the end of industrial robot 1 and used to detect and calculate the position deviation between the terminal head and the terminal base. The position deviation will drive robot 1 to align the terminal head with the terminal base to complete the position correction. The YOLOv3, least square, and feature extraction algorithms are used in image processing. The accuracy of the YOLOv3 target detection model trained by self-made data set can reach more than 95% under different conditions. The detection period is within 65 ms. The experimental results show that the terminal assembly system designed in this paper has excellent reliability and assembly success rate. It also has a significant reference value for other terminals’ automatic buckling assemblies.

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Section: Terminal Head Alignmentmentioning

confidence: 99%

“…3 Machine vision is frequently used to position a component to be gripped accurately. [4][5][6][7] With the development of image processing, significant improvements have taken place in the manufacturing industry. [8][9][10][11] Wang et al 12 proposed a novel rail-guided multi-microrobotic system for the assembly of cellular structures.…”

Section: Introductionmentioning

confidence: 99%