May 3, 2024, 4:54 a.m. | Chuer Pan, Brian Okorn, Harry Zhang, Ben Eisner, David Held

cs.LG updates on arXiv.org arxiv.org

arXiv:2211.09325v3 Announce Type: replace-cross
Abstract: How do we imbue robots with the ability to efficiently manipulate unseen objects and transfer relevant skills based on demonstrations? End-to-end learning methods often fail to generalize to novel objects or unseen configurations. Instead, we focus on the task-specific pose relationship between relevant parts of interacting objects. We conjecture that this relationship is a generalizable notion of a manipulation task that can transfer to new objects in the same category; examples include the relationship between …

arxiv cs.ai cs.cv cs.lg cs.ro manipulation robot robot manipulation tax type

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