Adaptive tactile interaction transfer via digitally embroidered smart gloves
Name
s41467-024-45059-8.pdf
Description
Published version
Size
3.67 MB
Format
Adobe PDF
Checksum (MD5)
85d669bc1fe50c49c060128af99b3152
Author(s)
Luo, Yiyue
Liu, Chao
Lee, Young Joong
DelPreto, Joseph
Wu, Kui
Foshey, Michael
Rus, Daniela
Palacios, Tomás
Li, Yunzhu
Torralba, Antonio
Date Issued
January 29, 2024
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Citation
Luo, Y., Liu, C., Lee, Y.J. et al. Adaptive tactile interaction transfer via digitally embroidered smart gloves. Nat Commun 15, 868 (2024).
Version
Final published version
Abstract
Human-machine interfaces for capturing, conveying, and sharing tactile information across time and space hold immense potential for healthcare, augmented and virtual reality, human-robot collaboration, and skill development. To realize this potential, such interfaces should be wearable, unobtrusive, and scalable regarding both resolution and body coverage. Taking a step towards this vision, we present a textile-based wearable human-machine interface with integrated tactile sensors and vibrotactile haptic actuators that are digitally designed and rapidly fabricated. We leverage a digital embroidery machine to seamlessly embed piezoresistive force sensors and arrays of vibrotactile actuators into textiles in a customizable, scalable, and modular manner. We use this process to create gloves that can record, reproduce, and transfer tactile interactions. User studies investigate how people perceive the sensations reproduced by our gloves with integrated vibrotactile haptic actuators. To improve the effectiveness of tactile interaction transfer, we develop a machine-learning pipeline that adaptively models how each individual user reacts to haptic sensations and then optimizes haptic feedback parameters. Our interface showcases adaptive tactile interaction transfer through the implementation of three end-to-end systems: alleviating tactile occlusion, guiding people to perform physical skills, and enabling responsive robot teleoperation.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1038/s41467-024-45059-8
