神经形态工程学
计算机科学
编码
记忆电阻器
人工智能
感知
实时计算
计算机硬件
电气工程
人工神经网络
工程类
神经科学
生物化学
化学
生物
基因
作者
Meng Qi,Yanyun Ren,Tao Sun,Runze Xu,Ziyu Lv,Ye Zhou,Su‐Ting Han
出处
期刊:Science Advances
[American Association for the Advancement of Science]
日期:2025-06-06
卷期号:11 (23)
被引量:1
标识
DOI:10.1126/sciadv.adt3068
摘要
Anemotaxis behaviors inspired by rats have tremendous potential in efficiently processing perilous search and rescue operations in the physical world, but there is still lack of hardware components that can efficiently sense, encode, and recognize wind signal. Here, we report an artificial vibrissal system consisting of a self-powered carbon black sensor and threshold-switching HfO2 memristor. By integrating a forming HfO2 memristor with a self-powered angle-detecting hydro-voltaic sensor, the spiking sensory neuron can synchronously perceive and encode wind, humidity, and temperature signals into spikes with different frequencies. Furthermore, to validate the self-powered artificial vibrissal system with anemotaxis behavior, a robotic car with equipped artificial vibrissal system tracks trajectory toward the air source has been demonstrated. This design not only addresses the high energy consumption and low computing issues of traditional sensory system but also introduces the multimode functionalities, therefore promoting the construction of neuromorphic perception systems for neurorobotics.
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