Magnetic Array Assisted Triboelectric Nanogenerator Sensor for Real-Time Gesture Interaction
Corresponding Author: Chenguo Hu
Nano-Micro Letters,
Vol. 13 (2021), Article Number: 51
Abstract
In human-machine interaction, robotic hands are useful in many scenarios. To operate robotic hands via gestures instead of handles will greatly improve the convenience and intuition of human-machine interaction. Here, we present a magnetic array assisted sliding triboelectric sensor for achieving a real-time gesture interaction between a human hand and robotic hand. With a finger’s traction movement of flexion or extension, the sensor can induce positive/negative pulse signals. Through counting the pulses in unit time, the degree, speed, and direction of finger motion can be judged in real-time. The magnetic array plays an important role in generating the quantifiable pulses. The designed two parts of magnetic array can transform sliding motion into contact-separation and constrain the sliding pathway, respectively, thus improve the durability, low speed signal amplitude, and stability of the system. This direct quantization approach and optimization of wearable gesture sensor provide a new strategy for achieving a natural, intuitive, and real-time human-robotic interaction.
Highlights:
1 By counting the positive/negative pulses in unit time to sense the degree, speed, and direction of finger motion in real-time.
2 The magnetic array assisted sliding structure translates sliding motion into contact-separation thus improves the durability and low-speed signal amplitude.
3 The magnetic track constrains the sliding direction that greatly improves the stability.
Keywords
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References
X.J. Pu, H.Y. Guo, J. Chen, X. Wang, Y. Xi et al., Eye motion triggered self-powered mechnosensational communication system using triboelectric nanogenerator. Sci. Adv. 3(7), e1700694 (2017). https://doi.org/10.1126/sciadv.1700694
Y. Kim, A. Chortos, W.T. Xu, Y.X. Liu, J.Y. Oh et al., A bioinspired flexible organic artificial afferent nerve. Science 360(6392), 998–1003 (2018). https://doi.org/10.1126/science.aao0098
X. Pu, Q. Tang, W. Chen, Z. Huang, G. Liu et al., Flexible triboelectric 3D touch pad with unit subdivision structure for effective XY positioning and pressure sensing. Nano Energy 76, 105047 (2020). https://doi.org/10.1016/j.nanoen.2020.105047
C.R. Qiu, B. Wang, N. Zhang, S.J. Zhang, J.F. Liu et al., Transparent ferroelectric crystals with ultrahigh piezoelectricity. Nature 577(7790), 350–354 (2020). https://doi.org/10.1038/s41586-019-1891-y
S. Takamatsu, T. Lonjaret, E. Ismailova, A. Masuda, T. Itoh et al., Wearable keyboard using conducting polymer electrodes on textiles. Adv. Mater. 28(22), 4485–4488 (2016). https://doi.org/10.1002/adma.201504249
A.J. Bandodkar, P. Gutruf, J. Choi, K. Lee, Y. Sekine et al., Battery-free, skin-interfaced microfluidic/electronic systems for simultaneous electrochemical, colorimetric, and volumetric analysis of sweat. Sci. Adv. 5(1), eaav3294 (2019). https://doi.org/10.1126/sciadv.aav3294
G.Z. Yang, J. Bellingham, P.E. Dupont, P. Fischer, L. Floridi et al., The grand challenges of science robotics. Sci. Robot. 3(14), eaar7650 (2018). https://doi.org/10.1126/scirobotics.aar7650
M.L. Zhu, Z.D. Sun, Z.X. Zhang, Q.F. Shi, T.Y.Y. He et al., Haptic-feedback smart glove as a creative human-machine interface (HMI) for virtual/augmented reality applications. Sci. Adv. 6(19), eaaz8693 (2020). https://doi.org/10.1126/sciadv.aaz8693
T. D’Orazio, R. Marani, V. Reno, G. Cicirelli, Recent trends in gesture recognition: how depth data has improved classical approaches. Image Vis. Comput. 52, 56–72 (2016). https://doi.org/10.1016/j.imavis.2016.05.007
J.W. Jeong, W.H. Yeo, A. Akhtar, J.J.S. Norton, Y.J. Kwack et al., Materials and optimized designs for human-machine interfaces via epidermal electronics. Adv. Mater. 25(47), 6839–6846 (2013). https://doi.org/10.1002/adma.201301921
P.G. Jung, G. Lim, S. Kim, K. Kong, A wearable gesture recognition device for detecting muscular activities based on air-pressure sensors. IEEE Transac. Ind. Inform. 11(2), 485–494 (2015). https://doi.org/10.1109/TII.2015.2405413
S. Alavi, D. Arsenault, A. Whitehead, Quaternion-based gesture recognition using wireless wearable motion capture sensors. Sensors 16(5), 605 (2016). https://doi.org/10.3390/s16050605
K. Dong, J.A. Deng, W.B. Ding, A.C. Wang, P.H. Wang et al., Versatile core-sheath yarn for sustainable biomechanical energy harvesting and real-time human-interactive sensing. Adv. Energy Mater. 8(23), 1801114 (2018). https://doi.org/10.1002/aenm.201801114
R. Cao, X.J. Pu, X.Y. Du, W. Yang, J.N. Wang et al., Screen-printed washable electronic textiles as self-powered touch/gesture tribo-sensors for intelligent human-machine interaction. ACS Nano 12(6), 5190–5196 (2018). https://doi.org/10.1021/acsnano.8b02477
X. Pu, H. Guo, Q. Tang, J. Chen, L. Feng et al., Rotation sensing and gesture control of a robot joint via triboelectric quantization sensor. Nano Energy 54, 453–460 (2018). https://doi.org/10.1016/j.nanoen.2018.10.044
L. Xie, X. Chen, Z. Wen, Y. Yang, J. Shi et al., Spiral steel wire based fiber-shaped stretchable and tailorable triboelectric nanogenerator for wearable power source and active gesture sensor. Nano-Micro Lett. 11(1), 39 (2019). https://doi.org/10.1007/s40820-019-0271-3
F. Wen, Z.D. Sun, T.Y.Y. He, Q.F. Shi, M.L. Zhu et al., Machine learning glove using self-powered conductive superhydrophobic triboelectric textile for gesture recognition in VR/AR applications. Adv. Sci. 7(14), 2000261 (2020). https://doi.org/10.1002/advs.202000261
Q. Tang, X.J. Pu, Q.X. Zeng, H.M. Yang, J. Li et al., A strategy to promote efficiency and durability for sliding energy harvesting by designing alternating magnetic stripe arrays in triboelectric nanogenerator. Nano Energy 66, 104087 (2019). https://doi.org/10.1016/j.nanoen.2019.104087
D. Liu, X. Yin, H.Y. Guo, L.L. Zhou, X.Y. Li et al., A constant current triboelectric nanogenerator arising from electrostatic breakdown. Sci. Adv. 5(4), eaav6437 (2019). https://doi.org/10.1126/sciadv.aav6437
Z.L. Wang, A.C. Wang, On the origin of contact-electrification. Mater. Today 30, 34–51 (2019). https://doi.org/10.1016/j.mattod.2019.05.016
X.X. Chen, Z.Y. Ren, H. Guo, X.L. Cheng, H.X. Zhang, Self-powered flexible and transparent smart patch for temperature sensing. Appl. Phys. Lett. 116(4), 043902 (2020). https://doi.org/10.1063/1.5134526
Q. Tang, M.H. Yeh, G. Liu, S. Li, J. Chen et al., Whirligig-inspired triboelectric nanogenerator with ultrahigh specific output as reliable portable instant power supply for personal health monitoring devices. Nano Energy 47, 74–80 (2018). https://doi.org/10.1016/j.nanoen.2018.02.039
Z. Liu, H. Li, B.J. Shi, Y.B. Fan, Z.L. Wang, Z. Li, Wearable and implantable triboelectric nanogenerators. Adv. Funct. Mater. 29(20), 1808820 (2019). https://doi.org/10.1002/adfm.201808820
H.Y. Guo, X.J. Pu, J. Chen, Y. Meng, M.H. Yeh et al., A highly sensitive, self-powered triboelectric auditory sensor for social robotics and hearing aids. Sci. Robot. 3(20), eaat2516 (2018). https://doi.org/10.1126/scirobotics.aat2516
G.F. Cai, J.H. Ciou, Y.Z. Liu, Y. Jiang, P.S. Lee, Leaf-inspired multiresponsive MXene-based actuator for programmable smart devices. Sci. Adv. 5(7), eaaw7956 (2019). https://doi.org/10.1126/sciadv.aaw7956
G. Liu, L. Xiao, C. Chen, W. Liu, X. Pu et al., Power cables for triboelectric nanogenerator networks for large-scale blue energy harvesting. Nano Energy 75, 104975 (2020). https://doi.org/10.1016/j.nanoen.2020.104975
Z.M. Wang, J. An, J.H. Nie, J.J. Luo, J.J. Shao et al., A Self-powered angle sensor at nanoradian-resolution for robotic arms and personalized medicare. Adv. Mater. 32(32), 2001466 (2020). https://doi.org/10.1002/adma.202001466