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NOIR 2.0: Neural Signal Operated Intelligent Robots for Everyday Activities

arXiv 2511.20848 ↗First posted 25 Nov 2025cs.RO cs.AI cs.HCcited by 0

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Abstract (arXiv)

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%.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 17 of its 33 references that are in the map. First posted on arXiv 25 Nov 2025.

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References · 17

  1. 2022R3M: A Universal Visual Representation for Robot Manipulationcited by 678
  2. 2021CLIPort: What and Where Pathways for Robotic Manipulationcited by 617
  3. 2022Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulationcited by 545
  4. 2022Simple Open-Vocabulary Object Detection with Vision Transformerscited by 303
  5. 2021BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environmentscited by 161
  6. 2020Hierarchical Planning for Long-Horizon Manipulation with Geometric and Symbolic Scene Graphscited by 83
  7. 2022Learning and Retrieval from Prior Data for Skill-based Imitation Learningcited by 77
  8. 2021Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Taskscited by 75
  9. 2021StructFormer: Learning Spatial Structure for Language-Guided Semantic Rearrangement of Novel Objectscited by 57
  10. 2023Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasetscited by 56
  11. 2021Learning Neuro-Symbolic Relational Transition Models for Bilevel Planningcited by 43
  12. 2020Deep Affordance Foresight: Planning Through What Can Be Done in the Futurecited by 41
5 more
  1. 2022LEAGUE: Guided Skill Learning and Abstraction for Long-Horizon Manipulationcited by 32
  2. 2022Generalizable Task Planning through Representation Pretrainingcited by 19
  3. 2022STAP: Sequencing Task-Agnostic Policiescited by 17
  4. 2023Primitive Skill-based Robot Learning from Human Evaluative Feedbackcited by 15
  5. 2023NOIR: Neural Signal Operated Intelligent Robots for Everyday Activitiescited by 8

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