Wrinkle-Free Sewing with Robotics: The Future of Soft Material Manufacturing

Author:

Fontana E.,Farajtabar M.,Marchello G.,Lahoud M.,Abidi H.,Meddahi A.,Baizid K.,D’Imperio M.,Cannella F.

Abstract

AbstractSewing flexible materials such as textiles and clothing can be challenging due to their tendency to wrinkle easily and their non-linear mechanical behaviour. Conventional methods in industrial plants are performed by workers and can be labour-intensive and time-consuming. Therefore, the interest in robotic solutions has grown in the last decade. In this paper, we propose a flexible and reliable robotic solution that can autonomously remove wrinkles from fabric. This method was designed as a part of a robotic cell capable of sewing together two different textiles, used in the manufacturing of cyclist garments. The robotic system employs two compliant soft fingers to stretch the fabric and a vision system to identify the wrinkles to flatten. The design of the fingers is bio-inspired, mimicking the adaptability and dexterity of biological systems, hence improving the gripping performance while reducing the risk of damage to the fabric. The developed vision system performs instance segmentation to identify the wrinkles on the fabric, and then identifies the best places to apply the gripper to flatten the tissue. This two-step process is iterated until wrinkles on the surface do not affect the final sewn product. Such a methodology is highly flexible and has no hard requirements, as the vision system requires only an RGB camera, and the fingers are 3D-printed, an affordable and common manufacturing process. Consequently, the system proposed in this paper can be easily employed in a wide variety of industrial scenarios, improving the productivity and the welfare of the workers.

Publisher

Springer Nature Switzerland

Reference24 articles.

1. Jimenez, P., Torras, C.: Perception of cloth in assistive robotic manipulation tasks. Nat. Comput. 19, 409–431 (2020)

2. Lin, X., Wang, Y., Huang, Z., Held, D.: Learning visible connectivity dynamics for cloth smoothing. In: Conference on Robot Learning, 256–266 (2022)

3. Nocentini, O., Kim, J., Bashir, Z.M., Cavallo, F.: Learning-based control approaches for service robots on cloth manipulation and dressing assistance: a comprehensive review. J. NeuroEng. Rehabil. 19(1), 1–25 (2022)

4. Gershon, D.: Parallel process decomposition of a dynamic manipulation task: robotic sewing. IEEE Trans. Robot. Autom. 6(3), 357–367 (1990)

5. Yamazaki, K., Inaba, M.: A cloth detection method based on image wrinkle feature for daily assistive robots. In: Proceedings of the IAPR Conference on Machine Vision Applications (IAPR MVA 2009), Keio University, Yokohama, Japan, pp. 366–369 (2009)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Wrinkle Detection and Cloth Flattening through Deep Learning and Image Analysis as Assistive Technologies for Sewing;Proceedings of the 17th International Conference on PErvasive Technologies Related to Assistive Environments;2024-06-26

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3