The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Perception‐to‐Cognition Tactile Sensing Based on Artificial‐Intelligence‐Motivated Human Full‐Skin Bionic Electronic Skin
Abstract
Traditional electronic skin (e‐skin), due to the lack of human‐brain‐like thinking and judging capability, is powerless to accelerate the pace to the intelligent era. Herein, artificial intelligence (AI)‐motivated full‐skin bionic (FSB) e‐skin consisting of the structures of human vellus hair, epidermis–dermis–hypodermis, is proposed. Benefiting from the double interlocked layered microcone structure and supercapacitive iontronic effect, the FSB e‐skin exhibits ultrahigh sensitivity of 8053.1 kPa−1 (<1 kPa), linear sensitivity of 3103.5 kPa−1 (1–34 kPa), and fast response/recovery time of <5.6 ms. In addition, it can realize the evolution from tactile perception to advanced intelligent tactile cognition after being equipped with a “brain”. First, static/dynamic contactless tactile perception is achieved based on the triboelectric effect of the vellus hair bionics. Second, the supercapacitive iontronic effect based structural bionics of the epidermis–dermis–hypodermis and a five‐layer multilayer perception (MLP) enable the general intelligent tactile cognition of gesture cognition and robot interaction. Most importantly, by making full use of the FSB e‐skin with a six‐layer MLP neural network, an advanced intelligent material cognition system is developed for real‐time cognition of the object material species and locations via one contact, which surpasses the capability of humans.
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Citations
Cites
Pursuing prosthetic electronic skin
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Coding and use of tactile signals from the fingertips in object manipulation tasks
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A flexible and highly sensitive strain-gauge sensor using reversible interlocking of nanofibres
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Reviving Vibration Energy Harvesting and Self-Powered Sensing by a Triboelectric Nanogenerator
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Self-citationElectronic skins and machine learning for intelligent soft robots
Shih, B., Shah, D., Li, J., Thuruthel, T. G., Park, Y.-L., Iida, F., Bao, Z., Kramer-Bottiglio, R., & Tolley, M. T. (2020) · Science Robotics · doi:10.1126/scirobotics.aaz9239 · Cited by 715
Cited by
Xu, T., Song, Q., Liu, K., Liu, H., Pan, J., Liu, W., Dai, L., Zhang, M., Wang, Y., Si, C., et al. (2023) · Nano-Micro Letters · doi:10.1007/s40820-023-01073-x · Cited by 435
Toward an AI Era: Advances in Electronic Skins
Fu, X., Cheng, W., Wan, G., Yang, Z., & Tee, B. C. K. (2024) · Chemical Reviews · doi:10.1021/acs.chemrev.4c00049 · Cited by 172
Metadata
- Authors
- Niu, H., Li, H., Gao, S., Li, Y., Wei, X., Chen, Y., Yue, W., Zhou, W., & Shen, G.
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2022-06-22
- Volume
- 34
- Issue
- 31
- Pages
- e2202622-e2202622
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- OpenAlex
- W4282025839
- Cited by
- 434
- References
- 39
- FWCI
- 25.37
- Type
- journal article
- Language
- en
- Open access
- closed
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- Niu, H., Li, H., Gao, S., Li, Y., Wei, X., Chen, Y., Yue, W., Zhou, W., & Shen, G. (2022). Perception‐to‐Cognition Tactile Sensing Based on Artificial‐Intelligence‐Motivated Human Full‐Skin Bionic Electronic Skin. Advanced Materials. https://doi.org/10.1002/adma.202202622
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