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This report presents the debates, posters, and discussions of the Sim2Real workshop held in conjunction with the 2020 edition of the "Robotics: Science and System" conference.
Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A. Efros · 2017
Earlier work this paper cites.
Learning agile and dynamic motor skills for legged robots
Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy, Dario Bellicoso, Vassilios Tsounis, Vladlen Koltun, and Marco Hutter · 2019
Earlier work this paper cites.
Learning ambidextrous robot grasping policies
Jeffrey Mahler, Matthew Matl, Vishal Satish, Michael Danielczuk, Bill DeRose, Stephen McKinley, and Ken Goldberg · 2019
Earlier work this paper cites.
Solving rubik’s cube with a robot hand, 2019
OpenAI, Ilge Akkaya, Marcin Andrychowicz, Maciek Chociej, Mateusz Litwin, Bob McGrew, Arthur Petron, Alex Paino, Matthias Plappert, Glenn Powell, Raphael Ribas, Jonas Schneider, Nikolas Tezak, Jerry Tworek, Peter Welinder, Lilian Weng, Qiming Yuan, Wojciech Zaremba, and Lei Zhang · 2019
Earlier work this paper cites.
Solving rubik’s cube with a robot hand, 2019
OpenAI, Ilge Akkaya, Marcin Andrychowicz, Maciek Chociej, Mateusz Litwin, Bob McGrew, Arthur Petron, Alex Paino, Matthias Plappert, Glenn Powell, Raphael Ribas, Jonas Schneider, Nikolas Tezak, Jerry Tworek, Peter Welinder, Lilian Weng, Qiming Yuan, Wojciech Zaremba, and Lei Zhang · 2019
Earlier work this paper cites.
Modular latent space transfer with analytic manifold learning
R. Antonova, M. Maydanskiy, D. Kragic, S. Devlin, and K. Hofmann · 2020
Earlier work this paper cites.
How to sim2real with gaussian processes: Prior mean versus kernels as priors
R. Antonova, A. Rai, and D. Kragic · 2020
Earlier work this paper cites.
Learning to walk without dynamics randomization
J. Dao, H. Duan, K. Green, J. Hurst, and A. Fern · 2020
Earlier work this paper cites.
Blenderproc: Reducing the reality gap with photorealistic rendering
M. Denninger, M. Sundermeyer, D. Winkelbauer, D. Olefir, T. Hodan, Y. Zidan, M. Elbadrawy, M. Knauer, H. Katam, and A. Lodhi · 2020
Earlier work this paper cites.
An imitation from observation approach to sim-to-real transfer
S. Desai, I. Durugkar, H. Karnan, G. Warnell, J. Hanna, and P. Stone · 2020
Earlier work this paper cites.
Augmenting differentiable simulators with neural networks to close the sim2real gap
E. Heiden, D. Millard, E. Coumans, and G. Sukhatme · 2020
Cited alongside, same era.
Continual learning on incremental simulations for real-world robotic manipulation tasks
J. Josifovski, M. Malmir, N. Klarmann, and A. Knoll · 2020
Cited alongside, same era.
Sim2real predictivity: Does evaluation in simulation predict real-world performance?
A. Kadian, J. Truong, A. Gokaslan, A. Clegg, E. Wijmans, S. Lee, M. Savva, S. Chernova, and D. Batra · 2020
Cited alongside, same era.
Deep drone acrobatics
Elia Kaufmann, Antonio Loquercio, René Ranftl, Matthias Müller, Vladlen Koltun, and Davide Scaramuzza · 2020
Cited alongside, same era.
Accurate high fidelity simulations for training robot navigation policies for dense crowds using deep reinforcement learning
J. Liang, U. Patel, A. J. Sathyamoorthy, and D. Manocha · 2020
Cited alongside, same era.
Online bayessim for combined simulator parameter inference and policy improvement
R. Possas, F. Ramos, D. Fox, L. Barcelos, and R. Oliveira · 2020
Closest in time.
Rl-cyclegan: Reinforcement learning aware simulation-to-real, 2020
Kanishka Rao, Chris Harris, Alex Irpan, Sergey Levine, Julian Ibarz, and Mohi Khansari · 2020
Closest in time.
Cunas - curiosity-driven neural-augmented simulator
S. C. Raparthy, M. Mozifian, L. Paull, and F. Golemo · 2020
Closest in time.
The importance and the limitations of sim2real for robotic manipulation in precision agriculture
C. Rizzardo, S. Katyara, M. Fernandes, and F. Chen · 2020
Closest in time.
Learning to manipulate deformable objects without demonstrations
Y. Wu, W Yan, T. Kurutach, L. Pinto, and P. Abbeel · 2020
Closest in time.
Learning predictive representations for deformable objects with contrastive estimation
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Robust sim2real transfer by learning inverse dynamics of simulated systems
M. Malmir, J. Josifovski, N. Klarmann, and A. Knoll · 2020
Cited alongside, same era.
Inferring the material properties of granular media for robotic tasks, 2020
Carolyn Matl, Yashraj Narang, Ruzena Bajcsy, Fabio Ramos, and Dieter Fox · 2020
Cited alongside, same era.
On assessing the value of simulation for robotics
L. Paull and A. Courchesne · 2020
Cited alongside, same era.
Learning agile robotic locomotion skills by imitating animals, 2020
Xue Bin Peng, Erwin Coumans, Tingnan Zhang, Tsang-Wei Lee, Jie Tan, and Sergey Levine · 2020
Cited alongside, same era.
W. Yan, A. Vangipuram, P. Abbeel, and L. Pinto · 2020
Closest in time.
Sim2real learning of vision-based obstacle avoidance for robotic manipulators
K. Zhang, T. Zhang, J. Lin, and L. Bi · 2020
Closest in time.
Necessity for more realistic contact simulation
M. Zhang · 2020
Closest in time.
Sim-to-real transfer in deep reinforcement learning for robotics: a survey, 2020
Wenshuai Zhao, Jorge Peña Queralta, and Tomi Westerlund · 2020
Closest in time.