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While there have been significant strides in dexterous manipulation, most of it is limited to benchmark tasks like in-hand reorientation which are of limited utility in the real world.
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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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K. Shaw, A. Agarwal, and D. Pathak · 2023
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Dinov2: Learning robust visual features without supervision, 2023
M. Oquab, T. Darcet, T. Moutakanni, H. V. Vo, M. Szafraniec, V. Khalidov, P. Fernandez, D. Haziza, F. Massa, A. El-Nouby, R. Howes, P.-Y. Huang, H. Xu, V. Sharma, S.-W. Li, W. Galuba, M. Rabbat, M. Assran, N. Ballas, G. Synnaeve, I. Misra, H. Jegou, J. Mairal, P. Labatut, A. Joulin, and P. Bojanowski · 2023
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Walk these ways: Tuning robot control for generalization with multiplicity of behavior
G. B. Margolis and P. Agrawal · 2023
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Unidexgrasp: Universal robotic dexterous grasping via learning diverse proposal generation and goal-conditioned policy
Y. Xu, W. Wan, J. Zhang, H. Liu, Z. Shan, H. Shen, R. Wang, H. Geng, Y. Weng, J. Chen, T. Liu, L. Yi, and H. Wang · 2023
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ARCTIC: A dataset for dexterous bimanual hand-object manipulation
Z. Fan, O. Taheri, D. Tzionas, M. Kocabas, M. Kaufmann, M. J. Black, and O. Hilliges · 2023
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Learning dexterous manipulation from exemplar object trajectories and pre-grasps
S. Dasari, A. Gupta, and V. Kumar · 2023
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Affordances from human videos as a versatile representation for robotics
S. Bahl, R. Mendonca, L. Chen, U. Jain, and D. Pathak · 2023
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Affordance diffusion: Synthesizing hand-object interactions
Y. Ye, X. Li, A. Gupta, S. D. Mello, S. Birchfield, J. Song, S. Tulsiani, and S. Liu · 2023
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Learning continuous grasping function with a dexterous hand from human demonstrations
J. Ye, J. Wang, B. Huang, Y. Qin, and X. Wang · 2023
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