Intelligent Robotic Sensory System with Epidermis‐Dermis Bionic Electronic Skin for Autonomous Hardness/Softness‐Based Material Perception

Abstract Traditional electronic skin (e‐skin), due to the lack of human‐skin‐like complex sensitive structures and their derived autonomous perception and decision‐making capabilities of the tactile nervous system, makes it difficult to achieve performance and deep‐level intelligence comparable to human skin. Herein, a soft/hardware‐synergy‐motivated epidermis‐dermis bionic (EDB) e‐skin is proposed, inspired by the interlaced papillary projections between the epidermis and dermis. Benefiting from the interlocked microdome structures and the iontronic effect, the EDB e‐skin exhibits a maximum sensitivity of 1558.3 kPa −1 (<1 kPa), a low limit of detection of <0.01 Pa, and a fast response/recovery time of <5.6 ms. In addition, the feasibility of the hardness/softness‐based material perception technology is verified through test results and COMSOL finite element analysis. Further, after being equipped with a “tactile nervous system”, that is, hardware functional modules and terminal artificial neural networks, an intelligent robotic sensory system integrated with the fingertips is developed. With a single touch, this system can autonomously and in real‐time perceive different hardness/softness‐based materials, achieving abilities comparable to those of humans.

Authors

Institutions

Publication Details

Journal
Advanced Functional Materials
Published
2025-03-24
DOI
https://doi.org/10.1002/adfm.202500511
Citations
29
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
19.55

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intelligent Robotic Sensory System with Epidermis‐Dermis Bionic Electronic Skin for Autonomous Hardness/Softness‐Based Material Perception

Xijin Xu, Ning Li, Song Gao, Hongsen Niu et al.
29 citations
Advanced Functional Materials
Advanced Sensor and Energy Harvesting Materials
19.55
article

Intelligent Robotic Sensory System with Epidermis‐Dermis Bionic Electronic Skin for Autonomous Hardness/Softness‐Based Material Perception

Xijin Xu, Ning Li, Song Gao, Hongsen Niu, Hao Kan, Chengwen Wang, Hao Li, Yang Li, Jianwen Liu
article en
29 citations

Abstract

Abstract Traditional electronic skin (e‐skin), due to the lack of human‐skin‐like complex sensitive structures and their derived autonomous perception and decision‐making capabilities of the tactile nervous system, makes it difficult to achieve performance and deep‐level intelligence comparable to human skin. Herein, a soft/hardware‐synergy‐motivated epidermis‐dermis bionic (EDB) e‐skin is proposed, inspired by the interlaced papillary projections between the epidermis and dermis. Benefiting from the interlocked microdome structures and the iontronic effect, the EDB e‐skin exhibits a maximum sensitivity of 1558.3 kPa −1 (<1 kPa), a low limit of detection of <0.01 Pa, and a fast response/recovery time of <5.6 ms. In addition, the feasibility of the hardness/softness‐based material perception technology is verified through test results and COMSOL finite element analysis. Further, after being equipped with a “tactile nervous system”, that is, hardware functional modules and terminal artificial neural networks, an intelligent robotic sensory system integrated with the fingertips is developed. With a single touch, this system can autonomously and in real‐time perceive different hardness/softness‐based materials, achieving abilities comparable to those of humans.

Advanced Functional MaterialsVol. 35(35)
Shandong University (CN), University of Jinan (CN)
China Postdoctoral Science Foundation, Natural Science Foundation of Shandong Province
Openalex Percentile: Top 0%
Advanced Sensor and Energy Harvesting Materials
19.55
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.