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We introduce real-is-sim, a new approach to integrating simulation into behavior cloning pipelines.
Xpbd: Position-based simulation of compliant constrained dynamics
M. Macklin, M. Müller, and N. Chentanez · 2016
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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 via sim-to-sim: Data-efficient robotic grasping via randomized-to-canonical adaptation networks
S. James, P. Wohlhart, M. Kalakrishnan, D. Kalashnikov, A. Irpan, J. Ibarz, S. Levine, R. Hadsell, and K. Bousmalis · 2019
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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
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Jerk-limited real-time trajectory generation with arbitrary target states
L. Berscheid and T. Kröger · 2021
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Warp: A high-performance python framework for gpu simulation and graphics
M. Macklin · 2022
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Vision-based manipulators need to also see from their hands
K. Hsu, M. J. Kim, R. Rafailov, J. Wu, and C. Finn · 2022
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3d gaussian splatting for real-time radiance field rendering
B. Kerbl, G. Kopanas, T. Leimkühler, and G. Drettakis · 2023
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Learning fine-grained bimanual manipulation with low-cost hardware
T. Zhao, V. Kumar, S. Levine, and C. Finn · 2023
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Diffusion policy: Visuomotor policy learning via action diffusion
C. Chi, Z. Xu, S. Feng, E. Cousineau, Y. Du, B. Burchfiel, R. Tedrake, and S. Song · 2023
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Flow matching for generative modeling, 2023
Y. Lipman, R. T. Q. Chen, H. Ben-Hamu, M. Nickel, and M. Le · 2023
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Rvt: Robotic view transformer for 3d object manipulation
A. Goyal, J. Xu, Y. Guo, V. Blukis, Y.-W. Chao, and D. Fox · 2023
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Adaptsim: Task-driven simulation adaptation for sim-to-real transfer
A. Z. Ren, H. Dai, B. Burchfiel, and A. Majumdar · 2023
Cited alongside, same era.
TAPIR: Tracking any point with per-frame initialization and temporal refinement
C. Doersch, Y. Yang, M. Vecerik, D. Gokay, A. Gupta, Y. Aytar, J. Carreira, and A. Zisserman · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Physically embodied gaussian splatting: A visually learnt and physically grounded 3d representation for robotics
J. Abou-Chakra, K. Rana, F. Dayoub, and N. Suenderhauf · 2024
Cited alongside, same era.
Learning interactive real-world simulators
S. S. Yang, Y. Du, K. Ghasemipour, J. Tompson, L. Kaelbling, D. Schuurmans, and P. Abbeel · 2024
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Cloth-splatting: 3d cloth state estimation from RGB supervision
A. Longhini, M. Büsching, B. P. Duisterhof, J. Lundell, J. Ichnowski, M. Björkman, and D. Kragic · 2024
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Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis
J. Luiten, G. Kopanas, B. Leibe, and D. Ramanan · 2024
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J. Xu, W. Cheng, Y. Gao, X. Wang, S. Gao, and Y. Shan · 2024
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Instantsplat: Sparse-view gaussian splatting in seconds, 2024
Z. Fan, K. Wen, W. Cong, K. Wang, J. Zhang, X. Ding, D. Xu, B. Ivanovic, M. Pavone, G. Pavlakos, Z. Wang, and Y. Wang · 2024
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K. Rana, J. Abou-Chakra, S. Garg, R. Lee, I. Reid, and N. Suenderhauf · 2024
Cited alongside, same era.
Robot learning as an empirical science: Best practices for policy evaluation
H. Kress-Gazit, K. Hashimoto, N. Kuppuswamy, P. Shah, P. Horgan, G. Richardson, S. Feng, and B. Burchfiel · 2024
Cited alongside, same era.
Diffusion policy: Visuomotor policy learning via action diffusion
C. Chi, Z. Xu, S. Feng, E. Cousineau, Y. Du, B. Burchfiel, R. Tedrake, and S. Song · 2024
Cited alongside, same era.
What do we learn from a large-scale study of pre-trained visual representations in sim and real environments?
S. Silwal, K. Yadav, T. Wu, J. Vakil, A. Majumdar, S. Arnaud, C. Chen, V.-P. Berges, D. Batra, A. Rajeswaran, et al · 2024
Cited alongside, same era.
Habitat synthetic scenes dataset (hssd-200): An analysis of 3d scene scale and realism tradeoffs for objectgoal navigation
M. Khanna, Y. Mao, H. Jiang, S. Haresh, B. Shacklett, D. Batra, A. Clegg, E. Undersander, A. X. Chang, and M. Savva · 2024
Cited alongside, same era.
Reconciling reality through simulation: A real-to-sim-to-real approach for robust manipulation
M. T. Villasevil, A. Simeonov, Z. Li, A. Chan, T. Chen, A. Gupta, and P. Agrawal · 2024
Cited alongside, same era.
Learning robot soccer from egocentric vision with deep reinforcement learning
D. Tirumala, M. Wulfmeier, B. Moran, S. Huang, J. Humplik, G. Lever, T. Haarnoja, L. Hasenclever, A. Byravan, N. Batchelor, N. Sreendra, K. Patel, M. Gwira, F. Nori, M. Riedmiller, and N. Heess · 2024
Cited alongside, same era.
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Autoeval: Autonomous evaluation of generalist robot manipulation policies in the real world
Z. Zhou, P. Atreya, Y. L. Tan, K. Pertsch, and S. Levine · 2025
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Evaluating real-world robot manipulation policies in simulation
X. Li, K. Hsu, J. Gu, O. Mees, K. Pertsch, H. R. Walke, C. Fu, I. Lunawat, I. Sieh, S. Kirmani, S. Levine, J. Wu, C. Finn, H. Su, Q. Vuong, and T. Xiao · 2025
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Scalable real2sim: Physics-aware asset generation via robotic pick-and-place setups
N. Pfaff, E. Fu, J. Binagia, P. Isola, and R. Tedrake · 2025
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Transic: Sim-to-real policy transfer by learning from online correction
Y. Jiang, C. Wang, R. Zhang, J. Wu, and L. Fei-Fei · 2025
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Phystwin: Physics-informed reconstruction and simulation of deformable objects from videos
H. Jiang, H.-Y. Hsu, K. Zhang, H.-N. Yu, S. Wang, and Y. Li · 2025
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Pink: Python inverse kinematics based on Pinocchio, 2025
S. Caron, Y. De Mont-Marin, R. Budhiraja, S. H. Bang, I. Domrachev, and S. Nedelchev · 2025
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