@inproceedings {Pronobis2012a, title = {Large-scale Semantic Mapping and Reasoning with Heterogeneous Modalities}, 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.}, author = {Andrzej Pronobis and Patric Jensfelt}, month = {May}, year = {2012}, booktitle = {Proceedings of the 2012 IEEE International Conference on Robotics and Automation (ICRA'12)} }