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Extracting Zero-shot Common Sense from Large Language Models for Robot 3D Scene Understanding. (arXiv:2206.04585v1 [cs.RO])
cs.CL updates on arXiv.org arxiv.org
Semantic 3D scene understanding is a problem of critical importance in
robotics. While significant advances have been made in simultaneous
localization and mapping algorithms, robots are still far from having the
common sense knowledge about household objects and their locations of an
average human. We introduce a novel method for leveraging common sense embedded
within large language models for labelling rooms given the objects contained
within. This algorithm has the added benefits of (i) requiring no task-specific
pre-training (operating entirely …
3d arxiv language language models large language models robot sense understanding