Figure 1. Overview of this research: (a) This system uses a robotic arm with a sensor head that has a simulated finger. The robotic arm slides the sensor head across fabric surfaces with controlled movements. The sensor head integrates two omnidirectional microphones, one triaxial accelerometer, and one load cell. (b) When the user places clothing on the attachment, the system automatically records multimodal tactile data under preset conditions for force applied to the garment, sliding speed, and sliding direction (8 directions, 5 speeds, and 2 kinds of force). The recorded data consists of frictional audio signals, surface images, and acceleration. (c) This system can contribute to investigating clothing quality and reproducing tactile sensations of clothing. † † :
Paper title: Tactile Data Recording System for Clothing with Motion-Controlled Robotic Sliding Abstract: The tactile sensation of clothing is critical to wearer comfort. To reveal physical properties that make clothing comfortable, systematic collection of tactile data during sliding motion is required. We propose a robotic arm-based system for collecting tactile data from intact garments. The system performs stroking measurements with a simulated fingertip while precisely controlling speed and direction, enabling creation of motion-labeled, multimodal tactile databases. Machine learning evaluation showed that including motion-related parameters improved identification accuracy for audio and acceleration data, demonstrating the efficacy of motion-related labels for characterizing clothing tactile sensation. This system provides a scalable, non-destructive method for capturing tactile data of clothing, contributing to future studies on fabric perception and reproduction. Passages referencing this figure: 3771452 † † isbn: 979-8-4007-2134-2/2025/12 † † ccs: Computing methodologies Neural networks † † ccs: Human-centered computing Haptic devices † † ccs: Information systems Multimedia databases Figure 1. We propose a robotic arm-based system for collecting tactile data from clothing (Fig. 1 ).