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Dexterous manipulation with contact-rich interactions is crucial for advanced robotics.
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Multi-goal reinforcement learning: Challenging robotics environments and request for research, 2018
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Dexterous manipulation with deep reinforcement learning: Efficient, general, and low-cost
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OpenAI: Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Jozefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, Alex Ray, et al · 2020
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Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, and Sergey Levine · 2020
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Wenlong Huang, Igor Mordatch, Pieter Abbeel, and Deepak Pathak · 2021
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Fei Ni, Jianye Hao, Yao Mu, Yifu Yuan, Yan Zheng, Bin Wang, and Zhixuan Liang · 2023
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Unidexgrasp++: Improving dexterous grasping policy learning via geometry-aware curriculum and iterative generalist-specialist learning
Weikang Wan, Haoran Geng, Yun Liu, Zikang Shan, Yaodong Yang, Li Yi, and He Wang · 2023
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Learning fine-grained bimanual manipulation with low-cost hardware
Tony Z Zhao, Vikash Kumar, Sergey Levine, and Chelsea Finn · 2023
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Claude 3.5 sonnet, 2024
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