Fetching the paper…
Reading the bibliography…
In this paper, we study the problem of enabling a vision-based robotic manipulation system to generalize to novel tasks, a long-standing challenge in robot learning.
Alvinn: An autonomous land vehicle in a neural network
D. A. Pomerleau · 1989
Earlier work this paper cites.
Robust estimation of a location parameter
P. J. Huber · 1992
Earlier work this paper cites.
Discovering optimal imitation strategies
A. Billard, Y. Epars, S. Calinon, S. Schaal, and G. Cheng · 2004
Earlier work this paper cites.
Learning movement primitives
S. Schaal, J. Peters, J. Nakanishi, and A. Ijspeert · 2005
Earlier work this paper cites.
Learning to walk through imitation
R. Chalodhorn, D. B. Grimes, K. Grochow, and R. P. Rao · 2007
Earlier work this paper cites.
A survey of robot learning from demonstration
B. D. Argall, S. Chernova, M. Veloso, and B. Browning · 2009
Earlier work this paper cites.
Learning and generalization of motor skills by learning from demonstration
P. Pastor, H. Hoffmann, T. Asfour, and S. Schaal · 2009
Earlier work this paper cites.
Learning collaborative manipulation tasks by demonstration using a haptic interface
S. Calinon, P. Evrard, E. Gribovskaya, A. Billard, and A. Kheddar · 2009
Earlier work this paper cites.
Learning stable non-linear dynamical systems with gaussian mixture models
S. Khansari-Zadeh and A. Billard · 2011
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.
Reinforcement and imitation learning via interactive no-regret learning
S. Ross and J. A. Bagnell · 2014
Earlier work this paper cites.
Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours
L. Pinto and A. Gupta · 2016
Earlier work this paper cites.
Identity mappings in deep residual networks
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
One-shot visual imitation learning via meta-learning
C. Finn, T. Yu, T. Zhang, P. Abbeel, and S. Levine · 2017
Earlier work this paper cites.
Y. Duan, M. Andrychowicz, B. C. Stadie, J. Ho, J. Schneider, I. Sutskever, P. Abbeel, and W. Zaremba · 2017
Earlier work this paper cites.
Dart: Noise injection for robust imitation learning
M. Laskey, J. Lee, R. Fox, A. Dragan, and K. Goldberg · 2017
Earlier work this paper cites.
J. Mahler, J. Liang, S. Niyaz, M. Laskey, R. Doan, X. Liu, J. A. Ojea, and K. Goldberg · 2017
Earlier work this paper cites.
Deep visual foresight for planning robot motion
C. Finn and S. Levine · 2017
Cited alongside, same era.
Task-embedded control networks for few-shot imitation learning
S. James, M. Bloesch, and A. J. Davison · 2018
Cited alongside, same era.
One-shot imitation from observing humans via domain-adaptive meta-learning
T. Yu, C. Finn, A. Xie, S. Dasari, T. Zhang, P. Abbeel, and S. Levine · 2018
Cited alongside, same era.
Vision-based multi-task manipulation for inexpensive robots using end-to-end learning from demonstration
R. Rahmatizadeh, P. Abolghasemi, L. Bölöni, and S. Levine · 2018
Cited alongside, same era.
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
Cited alongside, same era.
One-shot high-fidelity imitation: Training large-scale deep nets with rl
Vr-goggles for robots: Real-to-sim domain adaptation for visual control
J. Zhang, L. Tai, P. Yun, Y. Xiong, M. Liu, J. Boedecker, and W. Burgard · 2019
Later among the works it cites.
Robonet: Large-scale multi-robot learning
S. Dasari, F. Ebert, S. Tian, S. Nair, B. Bucher, K. Schmeckpeper, S. Singh, S. Levine, and C. Finn · 2019
Later among the works it cites.
Multilingual universal sentence encoder for semantic retrieval
Y. Yang, D. Cer, A. Ahmad, M. Guo, J. Law, N. Constant, G. H. Abrego, S. Yuan, C. Tar, Y.-H. Sung, et al · 2019
Later among the works it cites.
Causal confusion in imitation learning
P. de Haan, D. Jayaraman, and S. Levine · 2019
Later among the works it cites.
Learning one-shot imitation from humans without humans
A. Bonardi, S. James, and A. J. Davison · 2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
T. L. Paine, S. G. Colmenarejo, Z. Wang, S. Reed, Y. Aytar, T. Pfaff, M. W. Hoffman, G. Barth-Maron, S. Cabi, D. Budden, et al · 2018
Cited alongside, same era.
Zero-shot visual imitation
D. Pathak, P. Mahmoudieh, G. Luo, P. Agrawal, D. Chen, Y. Shentu, E. Shelhamer, J. Malik, A. A. Efros, and T. Darrell · 2018
Cited alongside, same era.
Scalable deep reinforcement learning for vision-based robotic manipulation
D. Kalashnikov, A. Irpan, P. Pastor, J. Ibarz, A. Herzog, E. Jang, D. Quillen, E. Holly, M. Kalakrishnan, V. Vanhoucke, et al · 2018
Cited alongside, same era.
Interactively picking real-world objects with unconstrained spoken language instructions
J. Hatori, Y. Kikuchi, S. Kobayashi, K. Takahashi, Y. Tsuboi, Y. Unno, W. Ko, and J. Tan · 2018
Cited alongside, same era.
Robot learning in homes: Improving generalization and reducing dataset bias
A. Gupta, A. Murali, D. Gandhi, and L. Pinto · 2018
Cited alongside, same era.
Sim2real viewpoint invariant visual servoing by recurrent control
F. Sadeghi, A. Toshev, E. Jang, and S. Levine · 2018
Cited alongside, same era.
Domain randomization and generative models for robotic grasping
J. Tobin, L. Biewald, R. Duan, M. Andrychowicz, A. Handa, V. Kumar, B. McGrew, A. Ray, J. Schneider, P. Welinder, et al · 2018
Cited alongside, same era.
Later among the works it cites.
Visual imitation made easy
S. Young, D. Gandhi, S. Tulsiani, A. Gupta, P. Abbeel, and L. Pinto · 2020
Later among the works it cites.
Transformers for one-shot visual imitation
S. Dasari and A. Gupta · 2020
Later among the works it cites.
Watch, try, learn: Meta-learning from demonstrations and reward
A. Zhou, E. Jang, D. Kappler, A. Herzog, M. Khansari, P. Wohlhart, Y. Bai, M. Kalakrishnan, S. Levine, and C. Finn · 2020
Later among the works it cites.
Language-conditioned imitation learning for robot manipulation tasks
S. Stepputtis, J. Campbell, M. Phielipp, S. Lee, C. Baral, and H. B. Amor · 2020
Later among the works it cites.
C. Lynch and P. Sermanet · 2020
Later among the works it cites.
Learning from interventions: Human-robot interaction as both explicit and implicit feedback
J. Spencer, S. Choudhury, M. Barnes, M. Schmittle, M. Chiang, P. Ramadge, and S. Srinivasa · 2020
Later among the works it cites.
Action image representation: Learning scalable deep grasping policies with zero real world data
M. Khansari, D. Kappler, J. Luo, J. Bingham, and M. Kalakrishnan · 2020
Later among the works it cites.
Active domain randomization
B. Mehta, M. Diaz, F. Golemo, C. J. Pal, and L. Paull · 2020
Later among the works it cites.
End-to-end learning of visual representations from uncurated instructional videos
A. Miech, J.-B. Alayrac, L. Smaira, I. Laptev, J. Sivic, and A. Zisserman · 2020
Later among the works it cites.
Zero-shot task adaptation using natural language
P. Goyal, R. J. Mooney, and S. Niekum · 2021
Later among the works it cites.
Actionable models: Unsupervised offline reinforcement learning of robotic skills
Y. Chebotar, K. Hausman, Y. Lu, T. Xiao, D. Kalashnikov, J. Varley, A. Irpan, B. Eysenbach, R. Julian, C. Finn, et al · 2021
Later among the works it cites.
Mt-opt: Continuous multi-task robotic reinforcement learning at scale
D. Kalashnikov, J. Varley, Y. Chebotar, B. Swanson, R. Jonschkowski, C. Finn, S. Levine, and K. Hausman · 2021
Later among the works it cites.
Retinagan: An object-aware approach to sim-to-real transfer
D. Ho, K. Rao, Z. Xu, E. Jang, M. Khansari, and Y. Bai · 2021
Later among the works it cites.