[en] Inspired by human skin, bionic tactile sensing is effectively promoting development and innovation in many fields with its flexible and efficient perception capabilities. Optical fiber, with its ability to perceive and transmit information and its flexible characteristics, is considered a promising solution in the field of tactile bionics. In this work, one optical fiber tactile sensing system based on a flexible PDMS-embedded optical fiber ring resonator (FRR) is designed for braille recognition, and the Pound-Drever-Hall (PDH) demodulation scheme is adopted to improve the detection sensitivity. Theoretical simulations and experimental verifications show that by adopting a bionic sliding approach and a Multilayer Perceptron Neural Network, a single FRR with a hardness gradient design can detect eight different tactile pressures in braille characters with an accuracy of 98.57%. Furthermore, after training and testing, the MLP-LSTM model classifies time series signals, thereby achieving completely accurate encoding of braille keywords and braille poems. The advantages of the optical fiber tactile sensing system in this study are that the high-quality factor FRR can detect subtle differences in braille dots, it is not affected by changes in optical power due to its relies on PDH frequency demodulation, and the application of machine learning algorithms can enhance the robustness to slight pressure errors and simplify the recognition process. This solution opens up what we believe is a new optical approach for bionic tactile perception and has important potential value in promoting human-computer interaction, smart medical care, and other fields.
Disciplines :
Materials science & engineering
Author, co-author :
Wang, Heng; Shenyang Aerospace University
Ma, Lin; Shenyang Aerospace University
Nie, Qin; Shenyang Aerospace University
HU, Xuehao ; Université de Mons - UMONS > Recherche > Service ERC Unit - Advanced Photonic
Li, Xiaoli; Beijing Normal University
Min, Rui; Beijing Normal University
Wang, Zhuo
Language :
English
Title :
Optical tactile sensor based on a flexible optical fiber ring resonator for intelligent braille recognition
Research Institute for Materials Science and Engineering
Funders :
National Key Research and Development Program of China National Natural Science Foundation of China Scientific research project of Liaoning Provincial Education Department
J. Wang, X. Liu, R. Li, et al., “Biomimetic strategies and technologies for artificial tactile sensory systems,” Trends Biotechnol. 41(7), 951–964 (2023).
Y. Li, M. Zhao, and Y. Yan et al., “Multifunctional biomimetic tactile system via a stick-slip sensing strategy for human–machine interactions,” npj Flexible Electron. 6(1), 46 (2022).
T. Kim, I. Hong, and M. Kim et al., “Ultra-stable and tough bioinspired crack-based tactile sensor for small legged robots,” npj Flexible Electron. 7(1), 22 (2023).
A. L. Trejos, J. Jayender, and M. Perri et al., “Robot-assisted tactile sensing for minimally invasive tumor localization,” The International Journal of Robotics Research 28(9), 1118–1133 (2009).
S. Li, X. Chen, and X. Li et al., “Bioinspired robot skin with mechanically gated electron channels for sliding tactile perception,” Sci. Adv. 8(48), eade0720 (2022).
H. Oh, G.-C. Yi, M. Yip, et al., “Scalable tactile sensor arrays on flexible substrates with high spatiotemporal resolution enabling slip and grip for closed-loop robotics,” Sci. Adv. 6(46), eabd7795 (2020).
N. Bai, Y. Xue, and S. Chen et al., “A robotic sensory system with high spatiotemporal resolution for texture recognition,” Nat. Commun. 14(1), 7121 (2023).
Y. Yan, Z. Hu, and Z. Yang et al., “Soft magnetic skin for super-resolution tactile sensing with force self-decoupling,” Sci. Robot. 6(51), eabc8801 (2021).
S. Isayed and R. Tahboub, “A review of optical braille recognition,” in 2015 2nd World Symposium on Web Applications and Networking (WSWAN), (IEEE, 2015), pp. 1–6.
B.-S. Park, S.-M. Im, and H. Lee et al., “Visual and tactile perception techniques for braille recognition,” Micro and Nano Syst Lett 11(1), 23 (2023).
P. Potdar, D. Hardman, E. Almanzor, et al., “High-speed tactile braille reading via biomimetic sliding interactions,” IEEE Robot. Autom. Practice 1, 1 (2024).
X.-F. Zhao, C.-Z. Hang, and H.-L. Lu et al., “A skin-like sensor for intelligent braille recognition,” Nano Energy 68, 104346 (2020).
Z. Gao, L. Chang, and B. Ren et al., “Enhanced braille recognition based on piezoresistive and piezoelectric dual-mode tactile sensors,” Sens. Actuators, A 366, 115000 (2024).
Y. Lu, D. Kong, and G. Yang et al., “Machine learning-enabled tactile sensor design for dynamic touch decoding,” Adv. Sci. 10(32), 2303949 (2023).
L. Huang, B. Luo, and X. Zou et al., “Research on efficient braille recognition based on the pair-u-shaped micro-nano optical fiber fingerprint-like tactile sensors,” Optics Laser Technology 179, 111349 (2024).
A. Prasad, S. Sebastian, and S. Asokan, “Diaphragm-micro-stylus-based fiber bragg grating tactile sensor,” IEEE Sens. J. 20(12), 6394–6399 (2020).
N. Yao, X. Wang, and S. Ma et al., “Single optical microfiber enabled tactile sensor for simultaneous temperature and pressure measurement,” Photonics Res. 10(9), 2040–2046 (2022).
Z. Wang, Z. Chen, and L. Ma et al., “Optical microfiber intelligent sensor: wearable cardiorespiratory and behavior monitoring with a flexible wave-shaped polymer optical microfiber,” ACS Appl. Mater. Interfaces 16(7), 8333–8345 (2024).
K. Xiao, Z. Wang, and Y. Ye et al., “Pdms-embedded wearable fbg sensors for gesture recognition and communication assistance,” Biomed. Opt. Express 15(3), 1892–1909 (2024).
X. Zhan, Z. Wang, and S. Kumar et al., “The application of pound-drever-hall technology in high resolution sensing-a review,” IEEE Sens. J. 23(7), 6427–6438 (2023).
Q. Liu, S. Zhao, and Z. He, “Improved pound-drever-hall techniques for high resolution optical fiber grating sensors,” J. Lightwave Technol. 39(12), 3846–3854 (2021).
X. Ma, Z. Cai, and C. Zhuang et al., “Integrated microcavity electric field sensors using pound-drever-hall detection,” Nat. Commun. 15(1), 1386 (2024).
Y.-S. Jang, J. Lim, and W. Wang et al., “Measurement of sub-fm/hz 1/2 displacement spectral densities in ultrahigh-q single-crystal microcavities with hertz-level lasers,” Photonics Res. 10(5), 1202–1209 (2022).
B. Culshaw and A. Kersey, “Fiber-optic sensing: A historical perspective,” J. Lightwave Technol. 26(9), 1064–1078 (2008).
K. J. Vahala, “Optical microcavities,” Nature 424(6950), 839–846 (2003).
L. Chen, S. Karilanova, and S. Chaki et al., “Spike timing–based coding in neuromimetic tactile system enables dynamic object classification,” Science 384(6696), 660–665 (2024).
B. Shih, D. Shah, and J. Li et al., “Electronic skins and machine learning for intelligent soft robots,” Sci. Robot. 5(41), eaaz9239 (2020).
I. Sutskever, O. Vinyals, and Q. V. Le, “Sequence to sequence learning with neural networks,” Advances in neural information processing systems 27, 1 (2014).
S. F. Müller-Cleve, V. Fra, and L. Khacef et al., “Braille letter reading: A benchmark for spatio-temporal pattern recognition on neuromorphic hardware,” Front. Neurosci. 16, 951164 (2022).
T. Li, A. Zhang, and M. Du et al., “A fingertip optical fiber composite sensor with conformal design for robotic perception of tactile force,” IEEE/ASME Transactions on Mechatronics 1, 1 (2024).
E. D. Black, “An introduction to pound–drever–hall laser frequency stabilization,” Am. J. Phys. 69(1), 79–87 (2001).
W. Liang, V. S. Ilchenko, and A. A. Savchenkov et al., “Resonant microphotonic gyroscope,” Optica 4(1), 114–117 (2017).
