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Large-scale Semantic Mapping and Reasoning with Heterogeneous Modalities

A. Pronobis, P. Jensfelt

In Proceedings of the 2012 IEEE International Conference on Robotics and Automation (ICRA), 2012.

About

This paper presents a probabilistic framework combining heterogeneous, uncertain, information such as object observations, shape, size, appearance of rooms and human input for semantic mapping. It abstracts multi-modal sensory information and integrates it with conceptual common-sense knowledge in a fully probabilistic fashion. It relies on the concept of spatial properties which make the semantic map more descriptive, and the system more scalable and better adapted for human interaction. A probabilistic graphical model, a chain-graph, is used to represent the conceptual information and perform spatial reasoning. Experimental results from online system tests in a large unstructured office environment highlight the system's ability to infer semantic room categories, predict existence of objects and values of other spatial properties as well as reason about unexplored space.

Highlights

BibTeX

@inproceedings{pronobis2012icra,
  author =       {Pronobis, Andrzej and Jensfelt, Patric},
  title =        {Large-scale Semantic Mapping and Reasoning with Heterogeneous Modalities},
  booktitle =    {Proceedings of the 2012 IEEE International Conference on Robotics and Automation (ICRA)},
  year =         2012,
  address =      {Saint Paul, MN, USA},
  month =        may,
  doi =          {10.1109/ICRA.2012.6224637},
  url =          {http://www.pronobis.pro/publications/pronobis2012icra}
}
© 2018. Copyright Andrzej Pronobis
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