@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},
  abstract =     {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.}
}