Abstract: Imitation Learning (IL) is a promising paradigm for learning dynamic manipulation of deformable objects since it does not depend on difficult-to-create accurate simulations of such objects.
Abstract: Most existing robotic grasp detection methods can achieve high accuracy in one single domain, but due to the differences in data distribution and object categories among different datasets, ...
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