用脑电波控制机器人完成日常任务，效率提升近一半。
NOIR 2.0: Neural Signal Operated Intelligent Robots for Everyday Activities
- 通过脑电图直接解码意图，实现人脑与机器的实时交互。
- 任务完成时间减少46%，仅需15次示范即可高效适配用户。
- 适合残障人士辅助、人机协作等场景，尤其看重易用性。
神经信号操作智能机器人（NOIR）系统是一种通用的脑-机器人接口，允许人类通过脑电信号控制机器人完成日常任务。该接口利用脑电图（EEG）将针对特定物体和期望动作的人类意图直接转化为机器人可执行的指令。本文提出NOIR 2.0，为NOIR的增强版本。NOIR 2.0采用更快速、更准确的脑解码算法，使任务完成时间减少46%。系统还引入少样本机器人学习算法，以适应个体用户并预测其意图。新的学习算法利用基础模型实现更高效的样本学习与适应（仅需15次示范，相较以往单次示范），整体人类操作时间显著降低65%。
原文摘要 · Abstract (English)
Neural Signal Operated Intelligent Robots (NOIR) system is a versatile brain-robot interface that allows humans to control robots for daily tasks using their brain signals. This interface utilizes electroencephalography (EEG) to translate human intentions regarding specific objects and desired actions directly into commands that robots can execute. We present NOIR 2.0, an enhanced version of NOIR. NOIR 2.0 includes faster and more accurate brain decoding algorithms, which reduce task completion time by 46%. NOIR 2.0 uses few-shot robot learning algorithms to adapt to individual users and predict their intentions. The new learning algorithms leverage foundation models for more sample-efficient learning and adaptation (15 demos vs. a single demo), significantly reducing overall human time by 65%.
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