Fixture-Free Automated Sewing System Using Dual-Arm Manipulator and High-Speed Fabric Edge Detection
Published:
K. Tang1, 3, X. Huang1, 3, A. Seino1, 2, F. Tokuda1, 2, A. Kobayashi1, 2, N. C. Tien1, 2, K. Kosuge1, 2, 3
1. Centre for Transformative Garment Production, Unites 1215 to 1220, 12/F, Building 19W, SPX1, Hong Kong Schience Park, Pak Shek Kok, N. T., Hong Kong SAR
2. Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR
3. Director of the JC STEM Lab of Robotics forSoft Materials, Department of Electrical and Electronic Engineering, Faculty of Engineering, The University of Hong Kong, Hong Kong SAR
Published in IEEE Robotics and Automation Letters (RA-L), 9 (2025) 8962 - 8969
DOI: 110.1109/LRA.2025.3592145
Download here.
- Abstract
- Inspired by human workers who perform complicated sewing tasks by repeating relatively simple operations, this letter proposes a fixture-free automated sewing system using a dual-arm manipulator and an ordinary sewing machine to sew two aligned fabrics along the edges, a common task in garment production. The proposed sewing system has a five-layer architecture: perception, dual-arm sewing Petri net, fundamental operations, control primitives, and hardware layers. This architecture decomposes various complex sewing tasks into sequences of fundamental operations. To meet the real-time requirement of automated sewing, a High-speed Fabric Edge Detection System (Hi-FEDS) is further proposed for the perception layer, which formulates the fabric edge detection problem for sewing as a classification problem of predefined distributed anchors. The anchor distribution is modeled by the Gaussian Uniform Mixture Model (GUMM). This method achieves high-speed fabric edge detection at an average of 120 FPS, with an average error of about one pixel. An experimental robotic sewing platform is developed, and the sewing results show that our system achieves high-quality sewing across fabrics of various shapes and materials.