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Compact Visuotactile World Models for Lifting: Prediction, Reward Alignment, and Force Constraints

Ma, Qinzhen
arXiv (All) · Papers
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artificial-intelligencerobotics
Accurate tactile forecasts need not improve force-constrained control. We study a 652,157-parameter action-conditioned visuotactile world model with matched behavior cloning, policy learning in imagination, independent reactive implicit Q-learning, and model-assisted force feedback. A fixed protocol
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