Making Sense of Indoor Spaces Using Semantic Web Mining and Situated Robot Perception

@inproceedings{Young2017MakingSO,
  title={Making Sense of Indoor Spaces Using Semantic Web Mining and Situated Robot Perception},
  author={Jay Young and Valerio Basile and Markus Suchi and Lars Kunze and Nick Hawes and Markus Vincze and Barbara Caputo},
  booktitle={AnSWeR@ESWC},
  year={2017}
}
Intelligent Autonomous Robots deployed in human environments must have understanding of the wide range of possible semantic identities associated with the spaces they inhabit – kitchens, living rooms, bathrooms, offices, garages, etc. We believe robots should learn this information through their own exploration and situated perception in order to uncover and exploit structure in their environments – structure that may not be apparent to human engineers, or that may emerge over time during a… 

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