2412.02676

N/A

Planning-Guided Diffusion Policy Learning for Generalizable Contact-Rich Bimanual Manipulation Contact-rich bimanual manipulation involves precise coordination of two arms to change object states through strategically selected contacts and motions. Due to the inherent complexity of these tasks, acquiring sufficient demonstration data and training policies that generalize to unseen scenarios remain a largely unresolved challenge. Building on recent advances in planning through contacts, we introduce Generalizable Planning-Guided Diffusion Policy Learning (GLIDE), an approach that effectively l

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• Pranav Jadhav

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