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Long-term topological localisation for service robots in dynamic environments using spectral maps
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2014 (English)In: IEEE International Conference on Intelligent Robots and Systems. Proceedings, ISSN 2153-0858, 4537-4542 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents a new approach for topological localisation of service robots in dynamic indoor environments. In contrast to typical localisation approaches that rely mainly on static parts of the environment, our approach makes explicit use of information about changes by learning and modelling the spatio-temporal dynamics of the environment where the robot is acting. The proposed spatio-temporal world model is able to predict environmental changes in time, allowing the robot to improve its localisation capabilities during long-term operations in populated environments. To investigate the proposed approach, we have enabled a mobile robot to autonomously patrol a populated environment over a period of one week while building the proposed model representation. We demonstrate that the experience learned during one week is applicable for topological localization even after a hiatus of three months by showing that the localization error rate is significantly lower compared to static environment representations.

Place, publisher, year, edition, pages
2014. 4537-4542 p.
Keyword [en]
Information use, Mobile robots, Robots, Topology
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-168539DOI: 10.1109/IROS.2014.6943205ScopusID: 2-s2.0-84911499250OAI: diva2:818019
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014; Palmer House Hilton HotelChicago; United States

QC 20150608

Available from: 2015-06-08 Created: 2015-06-04 Last updated: 2015-06-08Bibliographically approved

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Ekekrantz, Johan
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Computer Vision and Active Perception, CVAP
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