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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.
The berger rhythm: potential changes from the occipital lobes in man
E. D. Adrian and B. H. Matthews · 1934
Earlier work this paper cites.
Assessing self-maintenance: activities of daily living, mobility, and instrumental activities of daily living
S. Katz · 1983
Earlier work this paper cites.
A unified approach for motion and force control of robot manipulators: The operational space formulation
O. Khatib · 1987
Earlier work this paper cites.
Optimal spatial filtering of single trial eeg during imagined hand movement
H. Ramoser, J. Muller-Gerking, and G. Pfurtscheller · 2000
Earlier work this paper cites.
The bci competition 2003: progress and perspectives in detection and discrimination of eeg single trials
B. Blankertz, K.-R. Muller, G. Curio, T. M. Vaughan, G. Schalk, J. R. Wolpaw, A. Schlogl, C. Neuper, G. Pfurtscheller, T. Hinterberger, et al · 2004
Earlier work this paper cites.
L. van der Maaten and G. Hinton · 2008
Earlier work this paper cites.
Distance metric learning for large margin nearest neighbor classification
K. Q. Weinberger and L. K. Saul · 2009
Earlier work this paper cites.
Ros: an open-source robot operating system
M. Quigley, K. Conley, B. Gerkey, J. Faust, T. Foote, J. Leibs, R. Wheeler, A. Y. Ng, et al · 2009
Earlier work this paper cites.
Distance metric learning for large margin nearest neighbor classification
K. Q. Weinberger and L. K. Saul · 2009
Earlier work this paper cites.
A survey of stimulation methods used in ssvep-based bcis
D. Zhu, J. Bieger, G. G. Molina, and R. M. Aarts · 2010
Earlier work this paper cites.
Brain computer interfaces, a review
L. F. Nicolas-Alonso and J. Gomez-Gil · 2012
Earlier work this paper cites.
Eeg-based brain-controlled mobile robots: a survey
L. Bi, X.-A. Fan, and Y. Liu · 2013
Earlier work this paper cites.
On the quantification of ssvep frequency responses in human eeg in realistic bci conditions
R. Kuś, A. Duszyk, P. Milanowski, M. Łabecki, M. Bierzyńska, Z. Radzikowska, M. Michalska, J. Żygierewicz, P. Suffczyński, and P. J. Durka · 2013
Earlier work this paper cites.
Common spatial pattern and linear discriminant analysis for motor imagery classification
S.-L. Wu, C.-W. Wu, N. R. Pal, C.-Y. Chen, S.-A. Chen, and C.-T. Lin · 2013
Earlier work this paper cites.
Meg and eeg data analysis with mne-python
A. Gramfort, M. Luessi, E. Larson, D. A. Engemann, D. Strohmeier, C. Brodbeck, R. Goj, M. Jas, T. Brooks, L. Parkkonen, et al · 2013
Earlier work this paper cites.
Reducing the barrier to entry of complex robotic software: a moveit! case study, 2014
D. Coleman, I. Sucan, S. Chitta, and N. Correll · 2014
Earlier work this paper cites.
Self-supervised learning of grasp dependent tool affordances on the icub humanoid robot
T. Mar, V. Tikhanoff, G. Metta, and L. Natale · 2015
Earlier work this paper cites.
Noninvasive electroencephalogram based control of a robotic arm for reach and grasp tasks
J. Meng, S. Zhang, A. Bekyo, J. Olsoe, B. Baxter, and B. He · 2016
Earlier work this paper cites.
Electroencephalography (eeg) based control in assistive mobile robots: A review
N. M. Krishnan, M. Mariappan, K. Muthukaruppan, M. H. A. Hijazi, and W. W. Kitt · 2016
Earlier work this paper cites.
Ssvep based bmi for a meal assistance robot
C. J. Perera, I. Naotunna, C. Sadaruwan, R. A. R. C. Gopura, and T. D. Lalitharatne · 2016
Earlier work this paper cites.
Subject-based feature extraction by using fisher wpd-csp in brain–computer interfaces
B. Yang, H. Li, Q. Wang, and Y. Zhang · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
Imitation learning: A survey of learning methods
A. Hussein, M. M. Gaber, E. Elyan, and C. Jayne · 2017
Earlier work this paper cites.
Social eye gaze in human-robot interaction: a review
H. Admoni and B. Scassellati · 2017
Earlier work this paper cites.
Task level hierarchical system for bci-enabled shared autonomy
I. Akinola, B. Chen, J. Koss, A. Patankar, J. Varley, and P. Allen · 2017
Earlier work this paper cites.
Correcting robot mistakes in real time using eeg signals
A. F. Salazar-Gomez, J. DelPreto, S. Gil, F. H. Guenther, and D. Rus · 2017
Earlier work this paper cites.
Progress in eeg-based brain robot interaction systems
X. Mao, M. Li, W. Li, L. Niu, B. Xian, M. Zeng, and G. Chen · 2017
Earlier work this paper cites.
An improved discriminative filter bank selection approach for motor imagery eeg signal classification using mutual information
S. Kumar, A. Sharma, and T. Tsunoda · 2017
Cited alongside, same era.
Sparse bayesian learning for obtaining sparsity of eeg frequency bands based feature vectors in motor imagery classification
Y. Zhang, Y. Wang, J. Jin, and X. Wang · 2017
Cited alongside, same era.
Learning to segment affordances
T. Luddecke and F. Worgotter · 2017
Cited alongside, same era.
Object-based affordances detection with convolutional neural networks and dense conditional random fields
A. Nguyen, D. Kanoulas, D. G. Caldwell, and N. G. Tsagarakis · 2017
Cited alongside, same era.
Self-supervised learning of tool affordances from 3d tool representation through parallel som mapping
T. Mar, V. Tikhanoff, G. Metta, and L. Natale · 2017
Cited alongside, same era.
A survey on robots controlled by motor imagery brain-computer interfaces
J. Zhang and M. Wang · 2021
Later among the works it cites.
Hierarchical planning for long-horizon manipulation with geometric and symbolic scene graphs
Y. Zhu, J. Tremblay, S. Birchfield, and Y. Zhu · 2021
Later among the works it cites.
Deep affordance foresight: Planning through what can be done in the future
D. Xu, A. Mandlekar, R. Martín-Martín, Y. Zhu, S. Savarese, and L. Fei-Fei · 2021
Later among the works it cites.
R3m: A universal visual representation for robot manipulation
S. Nair, A. Rajeswaran, V. Kumar, C. Finn, and A. Gupta · 2021
Later among the works it cites.
One-shot affordance detection
H. Luo, W. Zhai, J. Zhang, Y. Cao, and D. Tao · 2021
Later among the works it cites.
Simple open-vocabulary object detection with vision transformers, 2022
M. Minderer, A. Gritsenko, A. Stone, M. Neumann, D. Weissenborn, A. Dosovitskiy, A. Mahendran, A. Arnab, M. Dehghani, Z. Shen, X. Wang, X. Zhai, T. Kipf, and N. Houlsby · 2022
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R. Zhang, Z. Liu, L. Zhang, J. A. Whritner, K. S. Muller, M. M. Hayhoe, and D. H. Ballard · 2018
Cited alongside, same era.
Human in the loop of robot learning: Eeg-based reward signal for target identification and reaching task
L. Schiatti, J. Tessadori, N. Deshpande, G. Barresi, L. C. King, and L. S. Mattos · 2018
Cited alongside, same era.
Control of a 7-dof robotic arm system with an ssvep-based bci
X. Chen, B. Zhao, Y. Wang, S. Xu, and X. Gao · 2018
Cited alongside, same era.
Simple nearest neighbor policy method for continuous control tasks, 2018
E. Mansimov and K. Cho · 2018
Cited alongside, same era.
Translating videos to commands for robotic manipulation with deep recurrent neural networks
A. Nguyen, D. Kanoulas, D. G. Caldwell, and N. G. Tsagarakis · 2018
Cited alongside, same era.
Motor imagery based brain–computer interfaces
R. Scherer and C. Vidaurre · 2018
Cited alongside, same era.
Leveraging human guidance for deep reinforcement learning tasks
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Learning neuro-symbolic relational transition models for bilevel planning
R. Chitnis, T. Silver, J. B. Tenenbaum, T. Lozano-Perez, and L. P. Kaelbling · 2022
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Augmenting reinforcement learning with behavior primitives for diverse manipulation tasks
S. Nasiriany, H. Liu, and Y. Zhu · 2022
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Structformer: Learning spatial structure for language-guided semantic rearrangement of novel objects
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Generalizable task planning through representation pretraining
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Guided skill learning and abstraction for long-horizon manipulation
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Taps: Task-agnostic policy sequencing
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Behavior-1k: A benchmark for embodied ai with 1,000 everyday activities and realistic simulation
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Learning and retrieval from prior data for skill-based imitation learning
S. Nasiriany, T. Gao, A. Mandlekar, and Y. Zhu · 2022
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One-shot transfer of affordance regions? affcorrs!
D. Hadjivelichkov, S. Zwane, M. P. Deisenroth, L. Agapito, and D. Kanoulas · 2022
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Behavior: Benchmark for everyday household activities in virtual, interactive, and ecological environments
S. Srivastava, C. Li, M. Lingelbach, R. Martín-Martín, F. Xia, K. E. Vainio, Z. Lian, C. Gokmen, S. Buch, K. Liu, et al · 2022
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A dual representation framework for robot learning with human guidance
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