机器人学
人工智能
伤害感受器
记忆电阻器
计算机科学
纳米技术
工程类
机器人
材料科学
医学
电气工程
伤害
内科学
受体
作者
Shengbo Wang,Mingchao Fang,Lekai Song,Cong Li,Jian Zhang,Arokia Nathan,Guohua Hu,Shuo Gao
出处
期刊:Cornell University - arXiv
日期:2024-06-13
标识
DOI:10.48550/arxiv.2406.09304
摘要
Artificial nociceptors, mimicking human-like stimuli perception, are of significance for intelligent robotics to work in hazardous and dynamic scenarios. One of the most essential characteristics of the human nociceptor is its self-adjustable attribute, which indicates that the threshold of determination of a potentially hazardous stimulus relies on environmental knowledge. This critical attribute has been currently omitted, but it is highly desired for artificial nociceptors. Inspired by these shortcomings, this article presents, for the first time, a Self-Directed Channel (SDC) memristor-based self-reconfigurable nociceptor, capable of perceiving hazardous pressure stimuli under different temperatures and demonstrates key features of tactile nociceptors, including 'threshold,' 'no-adaptation,' and 'sensitization.' The maximum amplification of hazardous external stimuli is 1000%, and its response characteristics dynamically adapt to current temperature conditions by automatically altering the generated modulation schemes for the memristor. The maximum difference ratio of the response of memristors at different temperatures is 500%, and this adaptability closely mimics the functions of biological tactile nociceptors, resulting in accurate danger perception in various conditions. Beyond temperature adaptation, this memristor-based nociceptor has the potential to integrate different sensory modalities by applying various sensors, thereby achieving human-like perception capabilities in real-world environments.
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