Fetching the paper…
Reading the bibliography…
We introduce GROOT, an imitation learning method for learning robust policies with object-centric and 3D priors.
A unified approach for motion and force control of robot manipulators: The operational space formulation
O. Khatib · 1987
Earlier work this paper cites.
Mixture density networks
C. M. Bishop · 1994
Earlier work this paper cites.
Hand-eye calibration
R. Horaud and F. Dornaika · 1995
Earlier work this paper cites.
A flexible new technique for camera calibration
Z. Zhang · 2000
Earlier work this paper cites.
A reduction of imitation learning and structured prediction to no-regret online learning
S. Ross, G. Gordon, and D. Bagnell · 2011
Earlier work this paper cites.
Learning to select and generalize striking movements in robot table tennis
K. Mülling, J. Kober, O. Kroemer, and J. Peters · 2013
Earlier work this paper cites.
Deep spatial autoencoders for visuomotor learning
C. Finn, X. Y. Tan, Y. Duan, T. Darrell, S. Levine, and P. Abbeel · 2016
Earlier work this paper cites.
Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
Earlier work this paper cites.
One-shot imitation learning
Y. Duan, M. Andrychowicz, B. Stadie, O. Jonathan Ho, J. Schneider, I. Sutskever, P. Abbeel, and W. Zaremba · 2017
Earlier work this paper cites.
Modern robotics
K. M. Lynch and F. C. Park · 2017
Earlier work this paper cites.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
C. R. Qi, L. Yi, H. Su, and L. J. Guibas · 2017
Earlier work this paper cites.
Open3d: A modern library for 3d data processing
Q.-Y. Zhou, J. Park, and V. Koltun · 2018
Earlier work this paper cites.
Deep imitation learning for complex manipulation tasks from virtual reality teleoperation
T. Zhang, Z. McCarthy, O. Jow, D. Lee, X. Chen, K. Goldberg, and P. Abbeel · 2018
Earlier work this paper cites.
Deep object pose estimation for semantic robotic grasping of household objects
J. Tremblay, T. To, B. Sundaralingam, Y. Xiang, D. Fox, and S. Birchfield · 2018
Earlier work this paper cites.
Deep object-centric representations for generalizable robot learning
C. Devin, P. Abbeel, T. Darrell, and S. Levine · 2018
Earlier work this paper cites.
Self-supervised correspondence in visuomotor policy learning
P. Florence, L. Manuelli, and R. Tedrake · 2019
Earlier work this paper cites.
Causal confusion in imitation learning
P. De Haan, D. Jayaraman, and S. Levine · 2019
Earlier work this paper cites.
Exploring the limitations of behavior cloning for autonomous driving
F. Codevilla, E. Santana, A. M. López, and A. Gaidon · 2019
Earlier work this paper cites.
Imitation learning via off-policy distribution matching
I. Kostrikov, O. Nachum, and J. Tompson · 2019
Earlier work this paper cites.
Deep object-centric policies for autonomous driving
D. Wang, C. Devin, Q.-Z. Cai, F. Yu, and T. Darrell · 2019
Earlier work this paper cites.
Monet: Unsupervised scene decomposition and representation
C. P. Burgess, L. Matthey, N. Watters, R. Kabra, I. Higgins, M. Botvinick, and A. Lerchner · 2019
Earlier work this paper cites.
Dynamic graph cnn for learning on point clouds
Y. Wang, Y. Sun, Z. Liu, S. E. Sarma, M. M. Bronstein, and J. M. Solomon · 2019
Cited alongside, same era.
Learning to generalize across long-horizon tasks from human demonstrations
A. Mandlekar, D. Xu, R. Martín-Martín, S. Savarese, and L. Fei-Fei · 2020
Cited alongside, same era.
Keypoints into the future: Self-supervised correspondence in model-based reinforcement learning
L. Manuelli, Y. Li, P. Florence, and R. Tedrake · 2020
Cited alongside, same era.
Fighting copycat agents in behavioral cloning from observation histories
C. Wen, J. Lin, T. Darrell, D. Jayaraman, and Y. Gao · 2020
Cited alongside, same era.
Graph-structured visual imitation
M. Sieb, Z. Xian, A. Huang, O. Kroemer, and K. Fragkiadaki · 2020
Cited alongside, same era.
Learning and retrieval from prior data for skill-based imitation learning
S. Nasiriany, T. Gao, A. Mandlekar, and Y. Zhu · 2022
Later among the works it cites.
Cliport: What and where pathways for robotic manipulation
M. Shridhar, L. Manuelli, and D. Fox · 2022
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 · 2022
Later among the works it cites.
Masked visual pre-training for motor control
T. Xiao, I. Radosavovic, T. Darrell, and J. Malik · 2022
Later among the works it cites.
Cacti: A framework for scalable multi-task multi-scene visual imitation learning
Z. Mandi, H. Bharadhwaj, V. Moens, S. Song, A. Rajeswaran, and V. Kumar · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
A. Zeng, P. Florence, J. Tompson, S. Welker, J. Chien, M. Attarian, T. Armstrong, I. Krasin, D. Duong, V. Sindhwani, et al · 2020
Cited alongside, same era.
Object-centric task and motion planning in dynamic environments
T. Migimatsu and J. Bohg · 2020
Cited alongside, same era.
Object-centric learning with slot attention
F. Locatello, D. Weissenborn, T. Unterthiner, A. Mahendran, G. Heigold, J. Uszkoreit, A. Dosovitskiy, and T. Kipf · 2020
Cited alongside, same era.
What matters in learning from offline human demonstrations for robot manipulation
A. Mandlekar, D. Xu, J. Wong, S. Nasiriany, C. Wang, R. Kulkarni, L. Fei-Fei, S. Savarese, Y. Zhu, and R. Martín-Martín · 2021
Cited alongside, same era.
Object-aware regularization for addressing causal confusion in imitation learning
J. Park, Y. Seo, C. Liu, L. Zhao, T. Qin, J. Shin, and T.-Y. Liu · 2021
Cited alongside, same era.
Emerging properties in self-supervised vision transformers
M. Caron, H. Touvron, I. Misra, H. Jégou, J. Mairal, P. Bojanowski, and A. Joulin · 2021
Cited alongside, same era.
Modular interactive video object segmentation: Interaction-to-mask, propagation and difference-aware fusion
H. K. Cheng, Y.-W. Tai, and C.-K. Tang · 2021
Cited alongside, same era.
Later among the works it cites.
On pre-training for visuo-motor control: Revisiting a learning-from-scratch baseline
N. Hansen, Z. Yuan, Y. Ze, T. Mu, A. Rajeswaran, H. Su, H. Xu, and X. Wang · 2022
Later among the works it cites.
S. Tyree, J. Tremblay, T. To, J. Cheng, T. Mosier, J. Smith, and S. Birchfield · 2022
Later among the works it cites.
Visuomotor control in multi-object scenes using object-aware representations
N. Heravi, A. Wahid, C. Lynch, P. Florence, T. Armstrong, J. Tompson, P. Sermanet, J. Bohg, and D. Dwibedi · 2022
Later among the works it cites.
Masked autoencoders for point cloud self-supervised learning
Y. Pang, W. Wang, F. E. Tay, W. Liu, Y. Tian, and L. Yuan · 2022
Later among the works it cites.
Vision-based manipulators need to also see from their hands
K. Hsu, M. J. Kim, R. Rafailov, J. Wu, and C. Finn · 2022
Later among the works it cites.
Diffusion policy: Visuomotor policy learning via action diffusion
C. Chi, S. Feng, Y. Du, Z. Xu, E. Cousineau, B. Burchfiel, and S. Song · 2023
Closest in time.
A. Kirillov, E. Mintun, N. Ravi, H. Mao, C. Rolland, L. Gustafson, T. Xiao, S. Whitehead, A. C. Berg, W.-Y. Lo, et al · 2023
Closest in time.
Dinov2: Learning robust visual features without supervision
M. Oquab, T. Darcet, T. Moutakanni, H. Vo, M. Szafraniec, V. Khalidov, P. Fernandez, D. Haziza, F. Massa, A. El-Nouby, et al · 2023
Closest in time.
Perceiver-actor: A multi-task transformer for robotic manipulation
M. Shridhar, L. Manuelli, and D. Fox · 2023
Closest in time.
Mimicplay: Long-horizon imitation learning by watching human play
C. Wang, L. Fan, J. Sun, R. Zhang, L. Fei-Fei, D. Xu, Y. Zhu, and A. Anandkumar · 2023
Closest in time.
Scaling robot learning with semantically imagined experience
T. Yu, T. Xiao, A. Stone, J. Tompson, A. Brohan, S. Wang, J. Singh, C. Tan, J. Peralta, B. Ichter, et al · 2023
Closest in time.
Genaug: Retargeting behaviors to unseen situations via generative augmentation
Z. Chen, S. Kiami, A. Gupta, and V. Kumar · 2023
Closest in time.
Open-world object manipulation using pre-trained vision-language models
A. Stone, T. Xiao, Y. Lu, K. Gopalakrishnan, K.-H. Lee, Q. Vuong, P. Wohlhart, B. Zitkovich, F. Xia, C. Finn, et al · 2023
Closest in time.
Libero: Benchmarking knowledge transfer for lifelong robot learning
B. Liu, Y. Zhu, C. Gao, Y. Feng, Q. Liu, Y. Zhu, and P. Stone · 2023
Closest in time.
Multi-view masked world models for visual robotic manipulation
Y. Seo, J. Kim, S. James, K. Lee, J. Shin, and P. Abbeel · 2023
Closest in time.