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Dexterous grasping in cluttered scenes presents significant challenges due to diverse object geometries, occlusions, and potential collisions.
Deep dynamics models for learning dexterous manipulation
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Solving rubik’s cube with a robot hand
OpenAI, I. Akkaya, M. Andrychowicz, M. Chociej, M. Litwin, B. McGrew, A. Petron, A. Paino, M. Plappert, G. Powell, R. Ribas, J. Schneider, N. Tezak, J. Tworek, P. Welinder, L. Weng, Q. Yuan, W. Zaremba, and L. Zhang · 1910
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P. Abbeel and A. Y. Ng · 2005
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I. M. Bullock and A. M. Dollar · 2011
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Distilling the knowledge in a neural network, 2015
G. Hinton, O. Vinyals, and J. Dean · 2015
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Optimal control with learned local models: Application to dexterous manipulation
V. Kumar, E. Todorov, and S. Levine · 2016
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Learning complex dexterous manipulation with deep reinforcement learning and demonstrations
A. Rajeswaran, V. Kumar, A. Gupta, J. Schulman, E. Todorov, and S. Levine · 2017
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Hindsight experience replay
M. Andrychowicz, F. Wolski, A. Ray, J. Schneider, R. Fong, P. Welinder, B. McGrew, J. Tobin, O. Pieter Abbeel, and W. Zaremba · 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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Proximal policy optimization algorithms
J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov · 2017
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Dexterous manipulation with deep reinforcement learning: Efficient, general, and low-cost
H. Zhu, A. Gupta, A. Rajeswaran, S. Levine, and V. Kumar · 2018
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Learning dexterous in-hand manipulation
O. M. Andrychowicz, B. Baker, M. Chociej, R. Jozefowicz, B. McGrew, J. Pachocki, A. Petron, M. Plappert, G. Powell, A. Ray, et al · 2020
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Crossing the gap: A deep dive into zero-shot sim-to-real transfer for dynamics
E. Valassakis, Z. Ding, and E. Johns · 2020
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Graspnet-1billion: A large-scale benchmark for general object grasping
H.-S. Fang, C. Wang, M. Gou, and C. Lu · 2020
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A system for general in-hand object re-orientation
T. Chen, J. Xu, and P. Agrawal · 2021
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Sim-to-real transfer for robotic manipulation with tactile sensory
Z. Ding, Y.-Y. Tsai, W. W. Lee, and B. Huang · 2021
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Within-hand manipulation planning and control for variable friction hands
G. Narayanan, J. A. Raj, A. Gandhi, A. A. Gupte, A. J. Spiers, and B. Calli · 2021
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Region-based planning for 3d within-hand-manipulation via variable friction robot fingers and extrinsic contacts
A. Sahin, A. J. Spiers, and B. Calli · 2021
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Isaac gym: High performance gpu-based physics simulation for robot learning
V. Makoviychuk, L. Wawrzyniak, Y. Guo, M. Lu, K. Storey, M. Macklin, D. Hoeller, N. Rudin, A. Allshire, A. Handa, et al · 2021
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Dexpoint: Generalizable point cloud reinforcement learning for sim-to-real dexterous manipulation
Y. Qin, B. Huang, Z.-H. Yin, H. Su, and X. Wang · 2022
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Dvgg: Deep variational grasp generation for dextrous manipulation
W. Wei, D. Li, P. Wang, Y. Li, W. Li, Y. Luo, and J. Zhong · 2022
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From one hand to multiple hands: Imitation learning for dexterous manipulation from single-camera teleoperation
Y. Qin, H. Su, and X. Wang · 2022
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Learning purely tactile in-hand manipulation with a torque-controlled hand
L. Sievers, J. Pitz, and B. Bäuml · 2022
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Diffusion policies as an expressive policy class for offline reinforcement learning
Z. Wang, J. J. Hunt, and M. Zhou · 2022
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Ugg: Unified generative grasping
J. Lu, H. Kang, H. Li, B. Liu, Y. Yang, Q. Huang, and G. Hua · 2024
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Efficient residual learning with mixture-of-experts for universal dexterous grasping
Z. Huang, H. Yuan, Y. Fu, and Z. Lu · 2024
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Dextrah-rgb: Visuomotor policies to grasp anything with dexterous hands
R. Singh, A. Allshire, A. Handa, N. Ratliff, and K. Van Wyk · 2024
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Dexgraspnet 2.0: Learning generative dexterous grasping in large-scale synthetic cluttered scenes
J. Zhang, H. Liu, D. Li, X. Yu, H. Geng, Y. Ding, J. Chen, and H. Wang · 2024
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Tilde: Teleoperation for dexterous in-hand manipulation learning with a deltahand
Z. Si, K. L. Zhang, Z. Temel, and O. Kroemer · 2024
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A. Ajay, Y. Du, A. Gupta, J. Tenenbaum, T. Jaakkola, and P. Agrawal · 2022
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Planning with diffusion for flexible behavior synthesis
M. Janner, Y. Du, J. B. Tenenbaum, and S. Levine · 2022
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Learning generalizable dexterous manipulation from human grasp affordance
Y.-H. Wu, J. Wang, and X. Wang · 2023
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Unidexgrasp++: Improving dexterous grasping policy learning via geometry-aware curriculum and iterative generalist-specialist learning
W. Wan, H. Geng, Y. Liu, Z. Shan, Y. Yang, L. Yi, and H. Wang · 2023
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A survey of imitation learning: Algorithms, recent developments, and challenges, 2023
M. Zare, P. M. Kebria, A. Khosravi, and S. Nahavandi · 2023
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Learning a universal human prior for dexterous manipulation from human preference
Z. Ding, Y. Chen, A. Z. Ren, S. S. Gu, Q. Wang, H. Dong, and C. Jin · 2023
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Diffusion policy: Visuomotor policy learning via action diffusion
C. Chi, S. Feng, Y. Du, Z. Xu, E. Cousineau, B. Burchfiel, and S. Song · 2023
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Graspxl: Generating grasping motions for diverse objects at scale
H. Zhang, S. Christen, Z. Fan, O. Hilliges, and J. Song · 2024
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3d diffusion policy
Y. Ze, G. Zhang, K. Zhang, C. Hu, M. Wang, and H. Xu · 2024
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p i _ 0 pi\_0 : A vision-language-action flow model for general robot control
K. Black, N. Brown, D. Driess, A. Esmail, M. Equi, C. Finn, N. Fusai, L. Groom, K. Hausman, B. Ichter, et al · 2024
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Bunny-visionpro: Real-time bimanual dexterous teleoperation for imitation learning, 2024
R. Ding, Y. Qin, J. Zhu, C. Jia, S. Yang, R. Yang, X. Qi, and X. Wang · 2024
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Fungrasp: Functional grasping for diverse dexterous hands
L. Huang, H. Zhang, Z. Wu, S. Christen, and J. Song · 2024
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Unidexfpm: Universal dexterous functional pre-grasp manipulation via diffusion policy
T. Wu, Y. Gan, M. Wu, J. Cheng, Y. Yang, Y. Zhu, and H. Dong · 2024
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Omni6dpose: A benchmark and model for universal 6d object pose estimation and tracking
J. Zhang, W. Huang, B. Peng, M. Wu, F. Hu, Z. Chen, B. Zhao, and H. Dong · 2024
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Sam 2: Segment anything in images and videos, 2024
N. Ravi, V. Gabeur, Y.-T. Hu, R. Hu, C. Ryali, T. Ma, H. Khedr, R. Rädle, C. Rolland, L. Gustafson, E. Mintun, J. Pan, K. V. Alwala, N. Carion, C.-Y. Wu, R. Girshick, P. Dollár, and C. Feichtenhofer · 2024
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Dexgrasp anything: Towards universal robotic dexterous grasping with physics awareness
Y. Zhong, Q. Jiang, J. Yu, and Y. Ma · 2025
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Dexgraspvla: A vision-language-action framework towards general dexterous grasping
Y. Zhong, X. Huang, R. Li, C. Zhang, Y. Liang, Y. Yang, and Y. Chen · 2025
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Robustdexgrasp: Robust dexterous grasping of general objects
H. Zhang, Z. Wu, L. Huang, S. Christen, and J. Song · 2025
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Sim-and-real co-training: A simple recipe for vision-based robotic manipulation
A. Maddukuri, Z. Jiang, L. Y. Chen, S. Nasiriany, Y. Xie, Y. Fang, W. Huang, Z. Wang, Z. Xu, N. Chernyadev, et al · 2025
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Sim-to-real reinforcement learning for vision-based dexterous manipulation on humanoids
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Variable-friction in-hand manipulation for arbitrary objects via diffusion-based imitation learning
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