机器人
人机交互
日常生活
膨胀的
接口(物质)
计算机科学
游戏娱乐
信号(编程语言)
脑-机接口
人工智能
脑电图
大脑活动与冥想
神经活动
机器人学
心理学
神经科学
艺术
视觉艺术
抗压强度
材料科学
气泡
最大气泡压力法
并行计算
政治学
法学
复合材料
程序设计语言
作者
Ruohan Zhang,Sharon Lee,Minjune Hwang,Ayano Hiranaka,Chen Wang,Wensi Ai,Jian Tan,Sharad Gupta,Yilun Hao,Geoffrey Levine,Ruohan Gao,Anthony M. Norcia,Feifei Li,Jiajun Wu
出处
期刊:Cornell University - arXiv
日期:2023-11-02
标识
DOI:10.48550/arxiv.2311.01454
摘要
We present Neural Signal Operated Intelligent Robots (NOIR), a general-purpose, intelligent brain-robot interface system that enables humans to command robots to perform everyday activities through brain signals. Through this interface, humans communicate their intended objects of interest and actions to the robots using electroencephalography (EEG). Our novel system demonstrates success in an expansive array of 20 challenging, everyday household activities, including cooking, cleaning, personal care, and entertainment. The effectiveness of the system is improved by its synergistic integration of robot learning algorithms, allowing for NOIR to adapt to individual users and predict their intentions. Our work enhances the way humans interact with robots, replacing traditional channels of interaction with direct, neural communication. Project website: https://noir-corl.github.io/.
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