Automatic Place Detection and Localization in Autonomous Robotics

A. Chella, I. Macaluso, Lorenzo Riano

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    7 Citations (Scopus)

    Abstract

    This paper presents an approach for the simultaneous learning and recognition of places applied to autonomous robotics. While noteworthy results have been achieved with respect to off-line training process for appearance-based navigation, novel issues arise when recognition and learning are simultaneous and unsupervised processes. The approach adopted here uses a Gaussian mixture model estimated by a novel incremental MML-EM to model the probability distribution of features extracted by image-preprocessing. A place detector decides which features belong to which place integrating odometric information and a hidden Markov model. Tests demonstrate that the proposed system performs as well as the ones relying on batch off-line environmental learning.
    Original languageEnglish
    Title of host publicationUnknown Host Publication
    Place of PublicationLOS ALAMITOS -- USA
    Pages741-746
    Number of pages7
    Publication statusPublished - 2007
    EventIEEE/RSJ International Conference on intelligent Robots and Systems, 2007 -
    Duration: 1 Jan 2007 → …

    Conference

    ConferenceIEEE/RSJ International Conference on intelligent Robots and Systems, 2007
    Period1/01/07 → …

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    Cite this

    Chella, A., Macaluso, I., & Riano, L. (2007). Automatic Place Detection and Localization in Autonomous Robotics. In Unknown Host Publication (pp. 741-746). LOS ALAMITOS -- USA.