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Human hands are capable of in-hand manipulation in the presence of different hand motions.
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A. Church, J. Lloyd, R. Hadsell, and N. Lepora · 2021
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Reducing tactile sim2real domain gaps via deep texture generation networks
Tactile gym 2.0: Sim-to-real deep reinforcement learning for comparing low-cost high-resolution robot touch
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T. Chen, M. Tippur, S. Wu, V. Kumar, E. Adelson, and P. Agrawal · 2023
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T. Jianu, D. F. Gomes, and S. Luo · 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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rl-games: A high-performance framework for reinforcement learning
D. Makoviichuk and V. Makoviychuk · 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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Soft Biomimetic Optical Tactile Sensing With the TacTip: A Review
N. F. Lepora · 2021
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On the feasibility of learning finger-gaiting in-hand manipulation with intrinsic sensing
G. Khandate, M. Haas-Heger, and M. Ciocarlie · 2022
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A system for general in-hand object re-orientation
T. Chen, J. Xu, and P. Agrawal · 2022
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Adaptive fingers coordination for robust grasp and in-hand manipulation under disturbances and unknown dynamics
F. Khadivar and A. Billard · 2023
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Real-time motion planning for in-hand manipulation with a multi-fingered hand
X. Gao, K. Yao, F. Khadivar, and A. Billard · 2023
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T. Pang, H. T. Suh, L. Yang, and R. Tedrake · 2023
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Dynamic handover: Throw and catch with bimanual hands
B. Huang, Y. Chen, T. Wang, Y. Qin, Y. Yang, N. Atanasov, and X. Wang · 2023
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Dextreme: Transfer of agile in-hand manipulation from simulation to reality
A. Handa, A. Allshire, V. Makoviychuk, A. Petrenko, R. Singh, J. Liu, D. Makoviichuk, K. Van Wyk, A. Zhurkevich, B. Sundaralingam, et al · 2023
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Neural feels with neural fields: Visuo-tactile perception for in-hand manipulation
S. Suresh, H. Qi, T. Wu, T. Fan, L. Pineda, M. Lambeta, J. Malik, M. Kalakrishnan, R. Calandra, M. Kaess, et al · 2023
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Rotating without seeing: Towards in-hand dexterity through touch
Z.-H. Yin, B. Huang, Y. Qin, Q. Chen, and X. Wang · 2023
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Estimator-coupled reinforcement learning for robust purely tactile in-hand manipulation
L. Röstel, J. Pitz, L. Sievers, and B. Bäuml · 2023
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Dextrous tactile in-hand manipulation using a modular reinforcement learning architecture
J. Pitz, L. Röstel, L. Sievers, and B. Bäuml · 2023
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Tacchi: A pluggable and low computational cost elastomer deformation simulator for optical tactile sensors
Z. Chen, S. Zhang, S. Luo, F. Sun, and B. Fang · 2023
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Efficient tactile simulation with differentiability for robotic manipulation
J. Xu, S. Kim, T. Chen, A. R. Garcia, P. Agrawal, W. Matusik, and S. Sueda · 2023
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Simulation, learning, and application of vision-based tactile sensing at large scale
Q. K. Luu, N. H. Nguyen, et al · 2023
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Bi-touch: Bimanual tactile manipulation with sim-to-real deep reinforcement learning
Y. Lin, A. Church, M. Yang, H. Li, J. Lloyd, D. Zhang, and N. F. Lepora · 2023
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Sim-to-real model-based and model-free deep reinforcement learning for tactile pushing
M. Yang, Y. Lin, A. Church, J. Lloyd, D. Zhang, D. A. Barton, and N. F. Lepora · 2023
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