机器人
计算机科学
闭环
触觉传感器
传入的
人工智能
神经科学
控制工程
生物
工程类
作者
Shuai Chen,Zhongliang Zhou,Kunqi Hou,Xihu Wu,Qiang He,Cindy G. Tang,Ting Li,Xiujuan Zhang,Jiansheng Jie,Zhiyi Gao,Nripan Mathews,Wei Lin Leong
标识
DOI:10.1038/s41467-024-51403-9
摘要
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. Intelligent artificial tactile system for neurorobotics remains challenging. Here, Chen et al. developed an artificial organic afferent nerve to implement slip recognition and prevention actions by learning the real-time spatial information of directional touch.
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