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Robot In-hand Dexterous Manipulation by Extracting Knowledge from Human Object Manipulation to Improve Robotic Autonomy and Dexterity
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How robots can extract and learn dexterous manipulation skills from human multimodal data, including motion, tactile, and visual signals.
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How multisensory AI, imitation learning, and reinforcement learning improve robotic autonomy, adaptability, and in-hand manipulation performance
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Key challenges and solutions in transferring human manipulation skills to real robotic systems for industrial, assistive, and healthcare applications
