Effect of Twisted-Yarn Architecture on Pressure and Proximity Sensing Characteristics of Textile Capacitive Sensors for Robotic Skin

2026-08-14

AI Summary

This study addresses the insufficient quantification of yarn-level structure–property relationships in textile capacitive sensors by developing a silver-coated yarn sensing platform. Integrating PDMS-coated multi-layer twisting with local contact modeling, this work systematically elucidates the trade-off mechanism between twist level, sensitivity, and detection range. The research validates yarn architecture as an effective tunable design parameter, yielding a four-layer sensor with a sensitivity of 0.1331 MPa⁻¹ and cyclic stability exceeding 15,000 cycles. Furthermore, successful integration into a robotic system achieves an end-to-end response time of 403 ms. These findings establish a novel paradigm for high-performance flexible tactile sensing, bridging the gap between microstructural engineering and macroscopic functional performance in wearable electronics.

Abstract

Textile-integrated capacitive sensors offer flexible and conformable tactile sensing for wearable electronics and human-robot interaction; however, the influence of yarn-level architecture on capacitive transduction characteristics remains insufficiently quantified. This work presents a textile capacitive sensing platform based on silver-coated yarns coated with polydimethylsiloxane and assembled into one-, two-, and four-layer twisted configurations. The influence of effective electrode overlap area and inter-fiber separation on the capacitive response is systematically investigated, enabling architecture-dependent tuning of pressure and proximity sensing characteristics. Pressure was calculated using the localized single-fiber contact area, corresponding to stresses of 0.4-3.9 MPa. Increasing the layer number improved mechanical strength and sensing performance: elongation at break increased from 37.5% to 62.5% and 85.0%, while the maximum load increased from 23.3 to 42.7 and 89.7 N. Sensitivity increased with layer number and frequency, reaching 0.1331 MPa$^{-1}$ for the four-layer sensor at 100 kHz. The four-layer configuration also exhibited low hysteresis, minimal thermal drift from 25 to 90 $^\circ$C, and stable operation over 15,000 cycles. Proximity detection ranges of 60, 50, and 40 mm were obtained for the one-, two-, and four-layer sensors, respectively, revealing an architecture-dependent sensitivity-range trade-off. A 4$\times$4 textile sensing array enabled spatial contact mapping, while robotic-arm integration demonstrated real-time touch and proximity detection with an end-to-end robotic system latency (from detection to robot reaction) of 403 ms. The results establish yarn architecture as a tunable design parameter governing the measurement characteristics of textile-integrated capacitive sensing systems.

Problem

• Textile capacitive sensors
• Yarn architecture
• Capacitive transduction
• Pressure sensing
• Proximity sensing

Innovation

• Twisted-Yarn Architecture
• Textile Capacitive Sensors
• Architecture-Dependent Tuning
• Robotic Skin
• Pressure and Proximity Sensing