NOIR 2.0: Neural Signal Operated Intelligent Robots for Everyday Activities

Tasha Kim, Yingke Wang, Hanvit Cho, Alex Hodges
11/25/2025
cs.ROcs.AIcs.HC

No official code found. Best implementation: MuniAngothu/-Neural-Signal-Operated-Intelligent-Robots-for-Everyday-Activities (0 stars, last commit 2025-01-25).

Abstract

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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MuniAngothu/-Neural-Signal-Operated-Intelligent-Robots-for-Everyday-ActivitiesCommunity72%
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Cite this paper

@article{kim2025noir,
  title  = {NOIR 2.0: Neural Signal Operated Intelligent Robots for Everyday Activities},
  author = {Tasha Kim and Yingke Wang and Hanvit Cho and Alex Hodges},
  year   = {2025},
  eprint = {2511.20848},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2511.20848v1}
}

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