IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-022-34324-3.html
   My bibliography  Save this article

Humanlike spontaneous motion coordination of robotic fingers through spatial multi-input spike signal multiplexing

Author

Listed:
  • Dong Gue Roe

    (Yonsei University)

  • Dong Hae Ho

    (Yonsei University)

  • Yoon Young Choi

    (University of Illinois at Urbana−Champaign)

  • Young Jin Choi

    (Yonsei University)

  • Seongchan Kim

    (Sungkyunkwan University)

  • Sae Byeok Jo

    (Sungkyunkwan University)

  • Moon Sung Kang

    (Sogang University)

  • Jong-Hyun Ahn

    (Yonsei University)

  • Jeong Ho Cho

    (Yonsei University)

Abstract

With advances in robotic technology, the complexity of control of robot has been increasing owing to fundamental signal bottlenecks and limited expressible logic state of the von Neumann architecture. Here, we demonstrate coordinated movement by a fully parallel-processable synaptic array with reduced control complexity. The synaptic array was fabricated by connecting eight ion-gel-based synaptic transistors to an ion gel dielectric. Parallel signal processing and multi-actuation control could be achieved by modulating the ionic movement. Through the integration of the synaptic array and a robotic hand, coordinated movement of the fingers was achieved with reduced control complexity by exploiting the advantages of parallel multiplexing and analog logic. The proposed synaptic control system provides considerable scope for the advancement of robotic control systems.

Suggested Citation

  • Dong Gue Roe & Dong Hae Ho & Yoon Young Choi & Young Jin Choi & Seongchan Kim & Sae Byeok Jo & Moon Sung Kang & Jong-Hyun Ahn & Jeong Ho Cho, 2023. "Humanlike spontaneous motion coordination of robotic fingers through spatial multi-input spike signal multiplexing," Nature Communications, Nature, vol. 14(1), pages 1-7, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-022-34324-3
    DOI: 10.1038/s41467-022-34324-3
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-34324-3
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-34324-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Irem Boybat & Manuel Le Gallo & S. R. Nandakumar & Timoleon Moraitis & Thomas Parnell & Tomas Tuma & Bipin Rajendran & Yusuf Leblebici & Abu Sebastian & Evangelos Eleftheriou, 2018. "Neuromorphic computing with multi-memristive synapses," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    2. Kaushik Roy & Akhilesh Jaiswal & Priyadarshini Panda, 2019. "Towards spike-based machine intelligence with neuromorphic computing," Nature, Nature, vol. 575(7784), pages 607-617, November.
    3. Yongsuk Choi & Seyong Oh & Chuan Qian & Jin-Hong Park & Jeong Ho Cho, 2020. "Vertical organic synapse expandable to 3D crossbar array," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    4. Tianda Fu & Xiaomeng Liu & Hongyan Gao & Joy E. Ward & Xiaorong Liu & Bing Yin & Zhongrui Wang & Ye Zhuo & David J. F. Walker & J. Joshua Yang & Jianhan Chen & Derek R. Lovley & Jun Yao, 2020. "Bioinspired bio-voltage memristors," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    5. Paschalis Gkoupidenis & Dimitrios A. Koutsouras & George G. Malliaras, 2017. "Neuromorphic device architectures with global connectivity through electrolyte gating," Nature Communications, Nature, vol. 8(1), pages 1-8, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Choi, Woo Sik & Jang, Jun Tae & Kim, Donguk & Yang, Tae Jun & Kim, Changwook & Kim, Hyungjin & Kim, Dae Hwan, 2022. "Influence of Al2O3 layer on InGaZnO memristor crossbar array for neuromorphic applications," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    2. Kwon, Osung & Kim, Sungjun & Agudov, Nikolay & Krichigin, Alexey & Mikhaylov, Alexey & Grimaudo, Roberto & Valenti, Davide & Spagnolo, Bernardo, 2022. "Non-volatile memory characteristics of a Ti/HfO2/Pt synaptic device with a crossbar array structure," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    3. Jiaqi Liu & Jiangdong Gong & Huanhuan Wei & Yameng Li & Haixia Wu & Chengpeng Jiang & Yuelong Li & Wentao Xu, 2022. "A bioinspired flexible neuromuscular system based thermal-annealing-free perovskite with passivation," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Koryazhkina, M.N. & Filatov, D.O. & Shishmakova, V.A. & Shenina, M.E. & Belov, A.I. & Antonov, I.N. & Kotomina, V.E. & Mikhaylov, A.N. & Gorshkov, O.N. & Agudov, N.V. & Guarcello, C. & Carollo, A. & S, 2022. "Resistive state relaxation time in ZrO2(Y)-based memristive devices under the influence of external noise," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    5. Seokho Seo & Beomjin Kim & Donghoon Kim & Seungwoo Park & Tae Ryong Kim & Junkyu Park & Hakcheon Jeong & See-On Park & Taehoon Park & Hyeok Shin & Myung-Su Kim & Yang-Kyu Choi & Shinhyun Choi, 2022. "The gate injection-based field-effect synapse transistor with linear conductance update for online training," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    6. Wang, Xueqin & Yu, Dong & Li, Tianyu & Jia, Ya, 2023. "Logistic stochastic resonance in the Hodgkin–Huxley neuronal system under electromagnetic induction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    7. Wang, Huan & Li, Yan-Fu, 2023. "Bioinspired membrane learnable spiking neural network for autonomous vehicle sensors fault diagnosis under open environments," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    8. Simon Wintersteller & Olesya Yarema & Dhananjeya Kumaar & Florian M. Schenk & Olga V. Safonova & Paula M. Abdala & Vanessa Wood & Maksym Yarema, 2024. "Unravelling the amorphous structure and crystallization mechanism of GeTe phase change memory materials," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    9. Zhenjia Chen & Zhenyuan Lin & Ji Yang & Cong Chen & Di Liu & Liuting Shan & Yuanyuan Hu & Tailiang Guo & Huipeng Chen, 2024. "Cross-layer transmission realized by light-emitting memristor for constructing ultra-deep neural network with transfer learning ability," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    10. Takuya Isomura & Kiyoshi Kotani & Yasuhiko Jimbo & Karl J. Friston, 2023. "Experimental validation of the free-energy principle with in vitro neural networks," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    11. Filippo Moro & Emmanuel Hardy & Bruno Fain & Thomas Dalgaty & Paul Clémençon & Alessio Prà & Eduardo Esmanhotto & Niccolò Castellani & François Blard & François Gardien & Thomas Mesquida & François Ru, 2022. "Neuromorphic object localization using resistive memories and ultrasonic transducers," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    12. Shuzhi Liu & Jianmin Zeng & Zhixin Wu & Han Hu & Ao Xu & Xiaohe Huang & Weilin Chen & Qilai Chen & Zhe Yu & Yinyu Zhao & Rong Wang & Tingting Han & Chao Li & Pingqi Gao & Hyunwoo Kim & Seung Jae Baik , 2023. "An ultrasmall organic synapse for neuromorphic computing," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    13. Rohit Abraham John & Yiğit Demirağ & Yevhen Shynkarenko & Yuliia Berezovska & Natacha Ohannessian & Melika Payvand & Peng Zeng & Maryna I. Bodnarchuk & Frank Krumeich & Gökhan Kara & Ivan Shorubalko &, 2022. "Reconfigurable halide perovskite nanocrystal memristors for neuromorphic computing," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    14. Yan Wang & Yue Gong & Shenming Huang & Xuechao Xing & Ziyu Lv & Junjie Wang & Jia-Qin Yang & Guohua Zhang & Ye Zhou & Su-Ting Han, 2021. "Memristor-based biomimetic compound eye for real-time collision detection," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    15. Pei-Yu Huang & Bi-Yi Jiang & Hong-Ji Chen & Jia-Yi Xu & Kang Wang & Cheng-Yi Zhu & Xin-Yan Hu & Dong Li & Liang Zhen & Fei-Chi Zhou & Jing-Kai Qin & Cheng-Yan Xu, 2023. "Neuro-inspired optical sensor array for high-accuracy static image recognition and dynamic trace extraction," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    16. Sophie Griggs & Adam Marks & Dilara Meli & Gonzague Rebetez & Olivier Bardagot & Bryan D. Paulsen & Hu Chen & Karrie Weaver & Mohamad I. Nugraha & Emily A. Schafer & Joshua Tropp & Catherine M. Aitchi, 2022. "The effect of residual palladium on the performance of organic electrochemical transistors," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    17. Ruomin Zhu & Sam Lilak & Alon Loeffler & Joseph Lizier & Adam Stieg & James Gimzewski & Zdenka Kuncic, 2023. "Online dynamical learning and sequence memory with neuromorphic nanowire networks," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    18. Francesco Barchi & Luca Zanatta & Emanuele Parisi & Alessio Burrello & Davide Brunelli & Andrea Bartolini & Andrea Acquaviva, 2021. "Spiking Neural Network-Based Near-Sensor Computing for Damage Detection in Structural Health Monitoring," Future Internet, MDPI, vol. 13(8), pages 1-22, August.
    19. Chenhao Wang & Xinyi Xu & Xiaodong Pi & Mark D. Butala & Wen Huang & Lei Yin & Wenbing Peng & Munir Ali & Srikrishna Chanakya Bodepudi & Xvsheng Qiao & Yang Xu & Wei Sun & Deren Yang, 2022. "Neuromorphic device based on silicon nanosheets," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    20. Zhou, Qian & Qi, Saibing & Ren, Cong, 2021. "Gene essentiality prediction based on chaos game representation and spiking neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-022-34324-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.