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In the context of imitation learning applied to dexterous robotic hands, the high complexity of the systems makes learning complex manipulation tasks challenging.
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2022
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Qin, Y., Wu, Y., Liu, S., Jiang, H., Yang, R., Fu, Y. & Wang, X. DexMV: Imitation Learning for Dexterous Manipulation from Human Videos. (2022)
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Fu, Z., Zhao, T. & Finn, C. Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation. (2024)
2024
Closest in time.
Wang, J., Qin, Y., Kuang, K., Korkmaz, Y., Gurumoorthy, A., Su, H. & Wang, X. CyberDemo: Augmenting Simulated Human Demonstration for Real-World Dexterous Manipulation. (2024)
2024
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Wang, C., Shi, H., Wang, W., Zhang, R., Fei-Fei, L. & Liu, C. DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation. (2024)
2024
Closest in time.
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2024
Closest in time.