Large-scale semantic mapping and reasoning with heterogeneous modalities
2012 (English)In: 2012 IEEE International Conference on Robotics and Automation (ICRA), IEEE Computer Society, 2012, 3515-3522 p.Conference paper (Refereed)
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 chaingraph, 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.
Place, publisher, year, edition, pages
IEEE Computer Society, 2012. 3515-3522 p.
, IEEE International Conference on Robotics and Automation, ISSN 2152-4092
Human interactions, Multi-modal, Office environments, Probabilistic framework, Probabilistic graphical models, Semantic map, Semantic mapping, Sensory information, Spatial properties, Spatial reasoning, Robotics, Semantics
Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-101527DOI: 10.1109/ICRA.2012.6224637ISI: 000309406703080ScopusID: 2-s2.0-84864465291ISBN: 978-146731403-9OAI: oai:DiVA.org:kth-101527DiVA: diva2:549254
IEEE International Conference on Robotics and Automation (ICRA) Location: St Paul, MN Date: May 14-18, 2012
FunderICT - The Next Generation
QC 201209042012-09-042012-08-302013-10-02Bibliographically approved