Deep Learning–Powered Robust Tactile Perception: Bridging Graphene Electronic Skin and Dynamic Decoding
Decoding algorithm–based approaches emerge as transformative technologies for artificial sensory systems, transcending traditional methods and enabling robust and versatile applications. Herein, the development of an electronic skin (e‐skin) that integrates multifunctional tactile sensing capabiliti...
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| Format: | Article |
| Language: | English |
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Wiley
2025-06-01
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| Series: | Advanced Intelligent Systems |
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| Online Access: | https://doi.org/10.1002/aisy.202400909 |
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| author | Gyeonghwa Heo Jusouk Yoon Jeonghwa Jeong Young Woo Kwon Suck Won Hong |
| author_facet | Gyeonghwa Heo Jusouk Yoon Jeonghwa Jeong Young Woo Kwon Suck Won Hong |
| author_sort | Gyeonghwa Heo |
| collection | DOAJ |
| description | Decoding algorithm–based approaches emerge as transformative technologies for artificial sensory systems, transcending traditional methods and enabling robust and versatile applications. Herein, the development of an electronic skin (e‐skin) that integrates multifunctional tactile sensing capabilities, including dynamic pressure sensing and continuous sliding touch detection, along with human–robot interface is reported. To address the limitations of early works on multifunctionality in strain sensors based on resistive values, the innovative scheme harnesses the synergy of facile e‐skin fabrication and advanced decoding algorithms, creating a robust stimuli‐responsive platform. At the core of the system lies a straightforward integration of e‐skin, achieved by generating laser‐induced graphene on a liquid‐crystal polymer film, followed by embedding the transfer‐printed conductive graphene layer into an elastomeric substrate. This streamlined methodology optimizes existing sensor arrays without the need for intricate material combinations or interconnections, avoiding susceptibility to damage. The advanced decoding algorithms bypass geometric engineering and complex numerical calculations within the deep learning hyper‐redundant system. In the experimental results, it is demonstrated that the e‐skin system successfully achieves a Braille‐readable e‐skin and a surgery‐enabled human–robot interface, highlighting the scalability and adaptability of the e‐skin in coordination with decoding algorithm systems. |
| format | Article |
| id | doaj-art-7d33cd50a8dd4f3583778e357dab39ef |
| institution | DOAJ |
| issn | 2640-4567 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Intelligent Systems |
| spelling | doaj-art-7d33cd50a8dd4f3583778e357dab39ef2025-08-20T03:21:31ZengWileyAdvanced Intelligent Systems2640-45672025-06-0176n/an/a10.1002/aisy.202400909Deep Learning–Powered Robust Tactile Perception: Bridging Graphene Electronic Skin and Dynamic DecodingGyeonghwa Heo0Jusouk Yoon1Jeonghwa Jeong2Young Woo Kwon3Suck Won Hong4Department of Optics and Mechatronics Engineering Department of Cogno‐Mechatronics Engineering College of Nanoscience and Nanotechnology Pusan National University Busan 46241 Republic of KoreaDepartment of Business Promotion Group Yaskawa Electric Korea Corporation Anyang 14118 Republic of KoreaDepartment of Optics and Mechatronics Engineering Department of Cogno‐Mechatronics Engineering College of Nanoscience and Nanotechnology Pusan National University Busan 46241 Republic of KoreaEngineering Research Center for Color‐Modulated Extra‐Sensory Perception Technology Pusan National University Busan 46241 Republic of KoreaDepartment of Optics and Mechatronics Engineering Department of Cogno‐Mechatronics Engineering College of Nanoscience and Nanotechnology Pusan National University Busan 46241 Republic of KoreaDecoding algorithm–based approaches emerge as transformative technologies for artificial sensory systems, transcending traditional methods and enabling robust and versatile applications. Herein, the development of an electronic skin (e‐skin) that integrates multifunctional tactile sensing capabilities, including dynamic pressure sensing and continuous sliding touch detection, along with human–robot interface is reported. To address the limitations of early works on multifunctionality in strain sensors based on resistive values, the innovative scheme harnesses the synergy of facile e‐skin fabrication and advanced decoding algorithms, creating a robust stimuli‐responsive platform. At the core of the system lies a straightforward integration of e‐skin, achieved by generating laser‐induced graphene on a liquid‐crystal polymer film, followed by embedding the transfer‐printed conductive graphene layer into an elastomeric substrate. This streamlined methodology optimizes existing sensor arrays without the need for intricate material combinations or interconnections, avoiding susceptibility to damage. The advanced decoding algorithms bypass geometric engineering and complex numerical calculations within the deep learning hyper‐redundant system. In the experimental results, it is demonstrated that the e‐skin system successfully achieves a Braille‐readable e‐skin and a surgery‐enabled human–robot interface, highlighting the scalability and adaptability of the e‐skin in coordination with decoding algorithm systems.https://doi.org/10.1002/aisy.202400909artificial sensory systemdeep learninghuman–robot interfacelaser‐induced graphenetactile sensor |
| spellingShingle | Gyeonghwa Heo Jusouk Yoon Jeonghwa Jeong Young Woo Kwon Suck Won Hong Deep Learning–Powered Robust Tactile Perception: Bridging Graphene Electronic Skin and Dynamic Decoding Advanced Intelligent Systems artificial sensory system deep learning human–robot interface laser‐induced graphene tactile sensor |
| title | Deep Learning–Powered Robust Tactile Perception: Bridging Graphene Electronic Skin and Dynamic Decoding |
| title_full | Deep Learning–Powered Robust Tactile Perception: Bridging Graphene Electronic Skin and Dynamic Decoding |
| title_fullStr | Deep Learning–Powered Robust Tactile Perception: Bridging Graphene Electronic Skin and Dynamic Decoding |
| title_full_unstemmed | Deep Learning–Powered Robust Tactile Perception: Bridging Graphene Electronic Skin and Dynamic Decoding |
| title_short | Deep Learning–Powered Robust Tactile Perception: Bridging Graphene Electronic Skin and Dynamic Decoding |
| title_sort | deep learning powered robust tactile perception bridging graphene electronic skin and dynamic decoding |
| topic | artificial sensory system deep learning human–robot interface laser‐induced graphene tactile sensor |
| url | https://doi.org/10.1002/aisy.202400909 |
| work_keys_str_mv | AT gyeonghwaheo deeplearningpoweredrobusttactileperceptionbridginggrapheneelectronicskinanddynamicdecoding AT jusoukyoon deeplearningpoweredrobusttactileperceptionbridginggrapheneelectronicskinanddynamicdecoding AT jeonghwajeong deeplearningpoweredrobusttactileperceptionbridginggrapheneelectronicskinanddynamicdecoding AT youngwookwon deeplearningpoweredrobusttactileperceptionbridginggrapheneelectronicskinanddynamicdecoding AT suckwonhong deeplearningpoweredrobusttactileperceptionbridginggrapheneelectronicskinanddynamicdecoding |