Fetching the paper…
Reading the bibliography…
In the context of deep learning for robotics, we show effective method of training a real robot to grasp a tiny sphere (1.37cm of diameter), with an original combination of system design choices.
Dex-net 1.0: A cloud-based network of 3d objects for robust grasp planning using a multi-armed bandit model with correlated rewards
Mahler, J., Pokorny, F. T., Hou, B., Roderick, M., Laskey, M., Aubry, M., Kohlhoff, K., Kröger, T., Kuffner, J., and Goldberg, K · 1964
Earlier work this paper cites.
Design and use paradigms for gazebo, an open-source multi-robot simulator
Koenig, N., and Howard, A · 2004
Earlier work this paper cites.
Robotic grasping of novel objects using vision
Saxena, A., Driemeyer, J., and Ng, A. Y · 2008
Earlier work this paper cites.
Efficient reductions for imitation learning
Ross, S., and Bagnell, D · 2010
Earlier work this paper cites.
A reduction of imitation learning and structured prediction to no-regret online learning
Ross, S., Gordon, G. J., and Bagnell, D · 2011
Earlier work this paper cites.
Continuous control with deep reinforcement learning
Lillicrap, T. P., Hunt, J. J., Pritzel, A., Heess, N., Erez, T., Tassa, Y., Silver, D., and Wierstra, D · 2015
Earlier work this paper cites.
Human-level control through deep reinforcement learning
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., et al · 2015
Earlier work this paper cites.
Deep reinforcement learning for robotic manipulation
Gu, S., Holly, E., Lillicrap, T. P., and Levine, S · 2016
Earlier work this paper cites.
Levine, S., Pastor, P., Krizhevsky, A., and Quillen, D · 2016
Cited alongside, same era.
Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours
Pinto, L., and Gupta, A · 2016
Cited alongside, same era.
Progressive Neural Networks
Rusu, A. A., Rabinowitz, C. N., Desjardins, G., Soyer, H., Kirkpatrick, J., Kavukcuoglu, K., Pascanu, R., and Hadsell, R · 2016
Cited alongside, same era.
Sim-to-real robot learning from pixels with progressive nets
Rusu, A. A., Vecerik, M., Rothörl, T., Heess, N., Pascanu, R., and Hadsell, R · 2016
Cited alongside, same era.
Mastering the game of go with deep neural networks and tree search
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al · 2016
Cited alongside, same era.
Deep reinforcement learning, decision making, and control
Levine, S., and Finn, C · 2017
Closest in time.
Mahler, J., Liang, J., Niyaz, S., Laskey, M., Doan, R., Liu, X., Ojea, J. A., and Goldberg, K · 2017
Closest in time.
Sim-to-real transfer of robotic control with dynamics randomization
Peng, X. B., Andrychowicz, M., Zaremba, W., and Abbeel, P · 2017
Closest in time.
Data-efficient deep reinforcement learning for dexterous manipulation
Popov, I., Heess, N., Lillicrap, T., Hafner, R., Barth-Maron, G., Vecerik, M., Lampe, T., Tassa, Y., Erez, T., and Riedmiller, M · 2017
Closest in time.
Mastering the game of go without human knowledge
Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., Hubert, T., Baker, L., Lai, M., Bolton, A., et al · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Reinforcement learning thorugh asynchronous advantage actor-critic on a gpu
Babaeizadeh, M., Frosio, I., Tyree, S., Clemons, J., and Kautz, J · 2017
Cited alongside, same era.
Inoue, T., Chaudhury, S., De Magistris, G., and Dasgupta, S · 2017
Cited alongside, same era.
Transferring end-to-end visuomotor control from simulation to real world for a multi-stage task
James, S., Davison, A. J., and Johns, E · 2017
Cited alongside, same era.
Closest in time.
Gplac: Generalizing vision-based robotic skills using weakly labeled images
Singh, A., Yang, L., and Levine, S · 2017
Closest in time.
Domain randomization for transferring deep neural networks from simulation to the real world
Tobin, J., Fong, R., Ray, A., Schneider, J., Zaremba, W., and Abbeel, P · 2017
Closest in time.