Autonomous Sewing Technology and System: A New Strategy by Integrating Soft Fingers and Machine Vision Technology

The garment manufacturing industry, being labor-intensive, has long faced challenges in automating the sewing process due to the flexibility and deformability of fabrics. This study proposes a novel strategy for automated sewing by integrating soft fingers and machine vision technology. Firstly, leveraging the flexibility and adjustability of soft fingers, combined with the motion characteristics of the sewing machine, a sewing model was established to achieve coordinated operation between the soft fingers and the sewing machine. Experimental results indicate that the fabric feeding speed and waiting time of the soft fingers are significantly correlated with the sewing speed and stitch density of the sewing machine, but not with the fabric properties. Secondly, machine vision technology was employed to inspect the quality of the sewn fabrics, achieving a classification accuracy of 97.84%. This study not only provides theoretical and technical support for the intelligent upgrading of the garment manufacturing industry but also lays the foundation for the automation of complex sewing processes such as quilting. Future research will further optimize the system’s performance and expand its applications in more complex sewing tasks.

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Publication Details

Journal
Textiles
Published
2025-10-08
DOI
https://doi.org/10.3390/textiles5040045
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Autonomous Sewing Technology and System: A New Strategy by Integrating Soft Fingers and Machine Vision Technology

Álvaro Ramírez-Gómez, Jinzhu Shen, Jianping Wang, Fan Zhang
Textiles
Industrial Vision Systems and Defect Detection
article

Autonomous Sewing Technology and System: A New Strategy by Integrating Soft Fingers and Machine Vision Technology

Álvaro Ramírez-Gómez, Jinzhu Shen, Jianping Wang, Fan Zhang
article en

Abstract

The garment manufacturing industry, being labor-intensive, has long faced challenges in automating the sewing process due to the flexibility and deformability of fabrics. This study proposes a novel strategy for automated sewing by integrating soft fingers and machine vision technology. Firstly, leveraging the flexibility and adjustability of soft fingers, combined with the motion characteristics of the sewing machine, a sewing model was established to achieve coordinated operation between the soft fingers and the sewing machine. Experimental results indicate that the fabric feeding speed and waiting time of the soft fingers are significantly correlated with the sewing speed and stitch density of the sewing machine, but not with the fabric properties. Secondly, machine vision technology was employed to inspect the quality of the sewn fabrics, achieving a classification accuracy of 97.84%. This study not only provides theoretical and technical support for the intelligent upgrading of the garment manufacturing industry but also lays the foundation for the automation of complex sewing processes such as quilting. Future research will further optimize the system’s performance and expand its applications in more complex sewing tasks.

TextilesVol. 5(4)
Tongji University (CN), Donghua University (CN), Suzhou Thermal Engineering Research Institute (CN), Universidad Politécnica de Madrid (ES)
Openalex Percentile: Top 60%
Industrial Vision Systems and Defect Detection
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Autonomous Sewing Technology and System: A New Strategy by Integrating Soft Fingers and Machine Vision Technology — Álvaro Ramírez-Gómez, Jinzhu Shen, et al. · Textiles (2025) | TGRS Research Map | TGRS