纺织品分类学与纺织品拉捻分类
Textile Taxonomy and Classification Using Pulling and Twisting
摘要：
纺织品属性的识别是高级机器人操作任务的重要里程碑，这些任务考虑与服装物品的交互，例如辅助穿衣，洗衣折叠，自动缝纫，纺织品回收和再利用。尽管大量的工作考虑这一类的可变形物体，许多开放的问题仍然存在。这些涉及到的选择和建模的感觉反馈，以及控制和规划的互动和操作策略。最重要的是，没有结构化的方法来研究和评估不同的方法，可以弥合机器人社区和纺织生产行业之间的差距。为此，我们概述了纺织工业中常用的纤维类型和生产方法的纺织品分类。我们根据分类设计数据集，并研究如何机器人的行动，如纺织品样品的拉伸和扭曲，可以用于分类。我们还从收集数据的可视化和可解释性的角度提供了重要的见解。
英文摘要：
Identification of textile properties is an important milestone toward advanced robotic manipulation tasks that consider interaction with clothing items such as assisted dressing, laundry folding, automated sewing, textile recycling and reusing. Despite the abundance of work considering this class of deformable objects, many open problems remain. These relate to the choice and modelling of the sensory feedback as well as the control and planning of the interaction and manipulation strategies. Most importantly, there is no structured approach for studying and assessing different approaches that may bridge the gap between the robotics community and textile production industry. To this end, we outline a textile taxonomy considering fiber types and production methods, commonly used in textile industry. We devise datasets according to the taxonomy, and study how robotic actions, such as pulling and twisting of the textile samples, can be used for the classification. We also provide important insights from the perspective of visualization and interpretability of the gathered data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
