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If we want to train robots in simulation before deploying them in reality, it seems natural and almost self-evident to presume that reducing the sim2real gap involves creating simulators of increasing fidelity (since reality is what it is).
Hierarchical task and motion planning in the now
L. P. Kaelbling and T. Lozano-Pérez · 2011
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Mujoco: A physics engine for model-based control
E. Todorov, T. Erez, and Y. Tassa · 2012
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ShapeNet: An information-rich 3D model repository
A. X. Chang, T. Funkhouser, L. Guibas, P. Hanrahan, Q. Huang, Z. Li, S. Savarese, M. Savva, S. Song, H. Su, et al · 2015
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Pybullet, a python module for physics simulation for games, robotics and machine learning
E. Coumans and Y. Bai · 2016
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Real-time loop closure in 2d lidar slam
W. Hess, D. Kohler, H. Rapp, and D. Andor · 2016
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Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot
S. Kuindersma, R. Deits, M. Fallon, A. Valenzuela, H. Dai, F. Permenter, T. Koolen, P. Marion, and R. Tedrake · 2016
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Matterport3d: Learning from rgb-d data in indoor environments
A. Chang, A. Dai, T. Funkhouser, M. Halber, M. Niessner, M. Savva, S. Song, A. Zeng, and Y. Zhang · 2017
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Domain randomization for transferring deep neural networks from simulation to the real world
J. Tobin, R. Fong, A. Ray, J. Schneider, W. Zaremba, and P. Abbeel · 2017
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Sim-to-real transfer of robotic control with dynamics randomization
X. B. Peng, M. Andrychowicz, W. Zaremba, and P. Abbeel · 2018
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On Evaluation of Embodied Navigation Agents
P. Anderson, A. Chang, D. S. Chaplot, A. Dosovitskiy, S. Gupta, V. Koltun, J. Kosecka, J. Malik, R. Mottaghi, M. Savva, et al · 2018
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Sim-to-real: Learning agile locomotion for quadruped robots
J. Tan, T. Zhang, E. Coumans, A. Iscen, Y. Bai, D. Hafner, S. Bohez, and V. Vanhoucke · 2018
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Bayesian optimization using domain knowledge on the atrias biped
A. Rai, R. Antonova, S. Song, W. Martin, H. Geyer, and C. Atkeson · 2018
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Gibson env: Real-world perception for embodied agents
F. Xia, A. R. Zamir, Z. He, A. Sax, J. Malik, and S. Savarese · 2018
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Habitat: A Platform for Embodied AI Research
M. Savva, A. Kadian, O. Maksymets, Y. Zhao, E. Wijmans, B. Jain, J. Straub, J. Liu, V. Koltun, J. Malik, D. Parikh, and D. Batra · 2019
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Closing the sim-to-real loop: Adapting simulation randomization with real world experience
Y. Chebotar, A. Handa, V. Makoviychuk, M. Macklin, J. Issac, N. Ratliff, and D. Fox · 2019
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Learning exploration policies for navigation
T. Chen, S. Gupta, and A. Gupta · 2019
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Multi-agent manipulation via locomotion using hierarchical sim2real
O. Nachum, M. Ahn, H. Ponte, S. Gu, and V. Kumar · 2019
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Learning fast adaptation with meta strategy optimization
W. Yu, J. Tan, Y. Bai, E. Coumans, and S. Ha · 2019
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Learning generalizable locomotion skills with hierarchical reinforcement learning
T. Li, N. Lambert, R. Calandra, F. Meier, and A. Rai · 2019
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Using deep reinforcement learning to learn high-level policies on the atrias biped
T. Li, H. Geyer, C. G. Atkeson, and A. Rai · 2019
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Learning agile and dynamic motor skills for legged robots
J. Hwangbo, J. Lee, A. Dosovitskiy, D. Bellicoso, V. Tsounis, V. Koltun, and M. Hutter · 2019
Cited alongside, same era.
Pyrobot: An open-source robotics framework for research and benchmarking
A. Murali, T. Chen, K. V. Alwala, D. Gandhi, L. Pinto, S. Gupta, and A. Gupta · 2019
Cited alongside, same era.
DD-PPO: Learning near-perfect pointgoal navigators from 2.5 billion frames
E. Wijmans, A. Kadian, A. Morcos, S. Lee, I. Essa, D. Parikh, M. Savva, and D. Batra · 2020
Cited alongside, same era.
Isaac Sim
Nvidia · 2020
Cited alongside, same era.
Habitat 2.0: Training home assistants to rearrange their habitat
A. Szot, A. Clegg, E. Undersander, E. Wijmans, Y. Zhao, J. Turner, N. Maestre, M. Mukadam, D. Chaplot, O. Maksymets, A. Gokaslan, V. Vondrus, S. Dharur, F. Meier, W. Galuba, A. Chang, Z. Kira, V. Koltun, J. Malik, M. Savva, and D. Batra · 2021
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igibson 1.0: a simulation environment for interactive tasks in large realistic scenes
B. Shen, F. Xia, C. Li, R. Martín-Martín, L. Fan, G. Wang, C. Pérez-D’Arpino, S. Buch, S. Srivastava, L. P. Tchapmi, M. E. Tchapmi, K. Vainio, J. Wong, L. Fei-Fei, and S. Savarese · 2021
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Brax–a differentiable physics engine for large scale rigid body simulation
C. D. Freeman, E. Frey, A. Raichuk, S. Girgin, I. Mordatch, and O. Bachem · 2021
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Habitat-matterport 3d dataset (hm3d): 1000 large-scale 3d environments for embodied ai
S. K. Ramakrishnan, A. Gokaslan, E. Wijmans, O. Maksymets, A. Clegg, J. Turner, E. Undersander, W. Galuba, A. Westbury, A. X. Chang, et al · 2021
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Robothor: An open simulation-to-real embodied AI platform
M. Deitke, W. Han, A. Herrasti, A. Kembhavi, E. Kolve, R. Mottaghi, J. Salvador, D. Schwenk, E. VanderBilt, M. Wallingford, et al · 2020
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ThreeDWorld: A platform for interactive multi-modal physical simulation
C. Gan, J. Schwartz, S. Alter, M. Schrimpf, J. Traer, J. De Freitas, J. Kubilius, A. Bhandwaldar, N. Haber, M. Sano, et al · 2020
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Rlbench: The robot learning benchmark & learning environment
S. James, Z. Ma, D. R. Arrojo, and A. J. Davison · 2020
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SAPIEN: A simulated part-based interactive environment
F. Xiang, Y. Qin, K. Mo, Y. Xia, H. Zhu, F. Liu, M. Liu, H. Jiang, Y. Yuan, H. Wang, L. Yi, A. X. Chang, L. J. Guibas, and H. Su · 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.
Learning navigation skills for legged robots with learned robot embeddings
J. Truong, D. Yarats, T. Li, F. Meier, S. Chernova, D. Batra, and A. Rai · 2020
Cited alongside, same era.
Learning quadrupedal locomotion over challenging terrain
J. Lee, J. Hwangbo, L. Wellhausen, V. Koltun, and M. Hutter · 2020
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Bi-directional domain adaptation for sim2real transfer of embodied navigation agents
J. Truong, S. Chernova, and D. Batra · 2021
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Success weighted by completion time: A dynamics-aware evaluation criteria for embodied navigation
N. Yokoyama, S. Ha, and D. Batra · 2021
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Rma: Rapid motor adaptation for legged robots
A. Kumar, Z. Fu, D. Pathak, and J. Malik · 2021
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Planning in learned latent action spaces for generalizable legged locomotion
T. Li, R. Calandra, D. Pathak, Y. Tian, F. Meier, and A. Rai · 2021
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Learning a state representation and navigation in cluttered and dynamic environments
D. Hoeller, L. Wellhausen, F. Farshidian, and M. Hutter · 2021
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Integrated task and motion planning
C. R. Garrett, R. Chitnis, R. Holladay, B. Kim, T. Silver, L. P. Kaelbling, and T. Lozano-Pérez · 2021
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SORNet: Spatial object-centric representations for sequential manipulation
W. Yuan, C. Paxton, K. Desingh, and D. Fox · 2021
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Model-based motion imitation for agile, diverse and generalizable quadupedal locomotion
T. Li, J. Won, S. Ha, and A. Rai · 2021
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Learning robust perceptive locomotion for quadrupedal robots in the wild
T. Miki, J. Lee, J. Hwangbo, L. Wellhausen, V. Koltun, and M. Hutter · 2022
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Habitat-web: Learning embodied object-search strategies from human demonstrations at scale
R. Ramrakhya, E. Undersander, D. Batra, and A. Das · 2022
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Coupling vision and proprioception for navigation of legged robots
Z. Fu, A. Kumar, A. Agarwal, H. Qi, J. Malik, and D. Pathak · 2022
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Learning to walk in minutes using massively parallel deep reinforcement learning
N. Rudin, D. Hoeller, P. Reist, and M. Hutter · 2022
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Efficient and interpretable robot manipulation with graph neural networks
Y. Lin, A. S. Wang, E. Undersander, and A. Rai · 2022
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Fast and efficient locomotion via learned gait transitions
Y. Yang, T. Zhang, E. Coumans, J. Tan, and B. Boots · 2022
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