Robotic Fabric Alignment System for Sewing Using Global Local Weighted ICP
2026-08-10 • Robotics
Robotics
AI summaryⓘ
The authors developed a new system to automatically align fabric pieces before sewing. Their method, called GLW-ICP, helps the system find the exact positions of fabric edges and sewing lines, even if parts are hidden or in different positions. By matching fabric points to their computer models, the system can adjust the fabric very precisely. Tests showed it can align fabric within millimeters, making it useful for real-world sewing tasks.
fabric alignmentpose estimationiterative closest point (ICP)GLW-ICPsewing linesCAD modelsocclusion handlingedge detectionautomated sewingpoint cloud matching
Authors
Wenbo Dong, Dipankar Bhattacharya Member, Kai Tang, Akinari Kobayashi, Fuyuki Tokuda, Akira Seino, Norman C. Tien, Kazuhiro Kosuge
Abstract
Accurate fabric alignment is a critical step that must be performed before sewing. This paper presents a novel automated fabric alignment system. The system estimates the poses of top and bottom fabric panels, lying flat and wrinkle-free in arbitrary positions, using a new Global Local Weighted Iterative Closest Point (GLW-ICP) method. The system then manipulates the top panel to achieve precise alignment at both edges and sewing lines. Unlike conventional approaches, GLW-ICP robustly aligns both global edges and local sewing lines by globally aligning fabric edge points and locally aligning sewing line points to their corresponding CAD model points, while removing unmatched points in occluded regions. Real-world experiments with various fabric shapes show that the system consistently achieves millimeter-level alignment accuracy under both occlusion and non-occlusion conditions, demonstrating its effectiveness and suitability for automated fabric alignment in practical scenarios.