Artificial organic afferent nerves enable closed-loop tactile feedback for intelligent robot.

Journal: Nature communications
PMID: 39147776

Abstract

The emulation of tactile sensory nerves to achieve advanced sensory functions in robotics with artificial intelligence is of great interest. However, such devices remain bulky and lack reliable competence to functionalize further synaptic devices with proprioceptive feedback. Here, we report an artificial organic afferent nerve with low operating bias (-0.6 V) achieved by integrating a pressure-activated organic electrochemical synaptic transistor and artificial mechanoreceptors. The dendritic integration function for neurorobotics is achieved to perceive directional movement of object, further reducing the control complexity by exploiting the distributed and parallel networks. An intelligent robot assembled with artificial afferent nerve, coupled with a closed-loop feedback program is demonstrated to rapidly implement slip recognition and prevention actions upon occurrence of object slippage. The spatiotemporal features of tactile patterns are well differentiated with a high recognition accuracy after processing spike-encoded signals with deep learning model. This work represents a breakthrough in mimicking synaptic behaviors, which is essential for next-generation intelligent neurorobotics and low-power biomimetic electronics.

Authors

  • Shuai Chen
    State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
  • Zhongliang Zhou
    Department of Computer Science, University of Georgia, Athens, GA, USA.
  • Kunqi Hou
    School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
  • Xihu Wu
    School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
  • Qiang He
    College of Biomass Science and Engineering, Healthy Food Evaluation Research Center, Sichuan University, Chengdu 610065, China.
  • Cindy G Tang
    School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
  • Ting Li
    Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Xiujuan Zhang
    Institute of Functional Nano and Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou, Jiangsu, 215123, P. R. China.
  • Jiansheng Jie
    Institute of Functional Nano and Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou, Jiangsu, 215123, P. R. China.
  • Zhiyi Gao
    CAS Key Laboratory of Magnetic Materials and Devices, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, PR China.
  • Nripan Mathews
    School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore. nripan@ntu.edu.sg.
  • Wei Lin Leong
    School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore. wlleong@ntu.edu.sg.

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