发表机构
The University of Hong Kong; Imperial College London; Tohoku University; Fukushima University; City University of Hong Kong（香港大学; 帝国理工学院; 东北大学; 福岛大学; 香港城市大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出采用GLW-ICP方法的机器人布料对位系统，可实现布料全局边缘与局部缝纫线的精准对齐，在有无遮挡下均达毫米级精度，适用于自动缝纫场景。
AI 中文摘要
准确的布料对位是缝纫前必须完成的关键步骤。本文提出一种新型自动布料对位系统，该系统采用新的全局局部加权迭代最近点（GLW-ICP）方法，估计任意位置平放且无褶皱的上层和下层布料片的位姿，随后操控上层布料片实现边缘与缝纫线的精准对位。与传统方法不同，GLW-ICP通过将布料边缘点全局对齐至对应CAD模型点、将缝纫线点局部对齐至对应CAD模型点，同时去除遮挡区域的未匹配点，实现对全局边缘和局部缝纫线的鲁棒对位。针对多种布料形状的实际实验表明，该系统在有遮挡和无遮挡条件下均持续达到毫米级对位精度，证明了其在实际场景中自动布料对位的有效性与适用性。
英文摘要
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.
Comments16 pages, 10 figures, https://bhattner143.github.io/rfas-glwicp.github.io/
Journal refIEEE Transactions on Automation Science and Engineering, vol. 23, pp. 13391-13406, July 2026
