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Learning Perceptual Concepts by Bootstrapping from Human Queries. (arXiv:2111.05251v3 [cs.RO] UPDATED)
July 5, 2022, 1:11 a.m. | Andreea Bobu, Chris Paxton, Wei Yang, Balakumar Sundaralingam, Yu-Wei Chao, Maya Cakmak, Dieter Fox
cs.LG updates on arXiv.org arxiv.org
When robots operate in human environments, it's critical that humans can
quickly teach them new concepts: object-centric properties of the environment
that they care about (e.g. objects near, upright, etc). However, teaching a new
perceptual concept from high-dimensional robot sensor data (e.g. point clouds)
is demanding, requiring an unrealistic amount of human labels. To address this,
we propose a framework called Perceptual Concept Bootstrapping (PCB). First, we
leverage the inherently lower-dimensional privileged information, e.g., object
poses and bounding boxes, available …
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