Adaptive tactile interaction transfer via digitally embroidered smart gloves
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,...
| Main Authors: | , , , , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer Science and Business Media LLC
2024
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| Online Access: | https://hdl.handle.net/1721.1/157680 |
| _version_ | 1824457886186602496 |
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| author | Luo, Yiyue Liu, Chao Lee, Young Joong DelPreto, Joseph Wu, Kui Foshey, Michael Rus, Daniela Palacios, Tomás Li, Yunzhu Torralba, Antonio Matusik, Wojciech |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Luo, Yiyue Liu, Chao Lee, Young Joong DelPreto, Joseph Wu, Kui Foshey, Michael Rus, Daniela Palacios, Tomás Li, Yunzhu Torralba, Antonio Matusik, Wojciech |
| author_sort | Luo, Yiyue |
| collection | MIT |
| description | 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. |
| first_indexed | 2025-02-19T04:17:07Z |
| format | Article |
| id | mit-1721.1/157680 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2025-02-19T04:17:07Z |
| publishDate | 2024 |
| publisher | Springer Science and Business Media LLC |
| record_format | dspace |
| spelling | mit-1721.1/1576802024-12-23T06:24:10Z Adaptive tactile interaction transfer via digitally embroidered smart gloves Luo, Yiyue Liu, Chao Lee, Young Joong DelPreto, Joseph Wu, Kui Foshey, Michael Rus, Daniela Palacios, Tomás Li, Yunzhu Torralba, Antonio Matusik, Wojciech Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 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. 2024-11-26T15:46:51Z 2024-11-26T15:46:51Z 2024-01-29 2024-11-26T15:35:13Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/157680 Luo, Y., Liu, C., Lee, Y.J. et al. Adaptive tactile interaction transfer via digitally embroidered smart gloves. Nat Commun 15, 868 (2024). en 10.1038/s41467-024-45059-8 Nature Communications Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ application/pdf Springer Science and Business Media LLC Springer Nature |
| spellingShingle | Luo, Yiyue Liu, Chao Lee, Young Joong DelPreto, Joseph Wu, Kui Foshey, Michael Rus, Daniela Palacios, Tomás Li, Yunzhu Torralba, Antonio Matusik, Wojciech Adaptive tactile interaction transfer via digitally embroidered smart gloves |
| title | Adaptive tactile interaction transfer via digitally embroidered smart gloves |
| title_full | Adaptive tactile interaction transfer via digitally embroidered smart gloves |
| title_fullStr | Adaptive tactile interaction transfer via digitally embroidered smart gloves |
| title_full_unstemmed | Adaptive tactile interaction transfer via digitally embroidered smart gloves |
| title_short | Adaptive tactile interaction transfer via digitally embroidered smart gloves |
| title_sort | adaptive tactile interaction transfer via digitally embroidered smart gloves |
| url | https://hdl.handle.net/1721.1/157680 |
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