Automatic Place Detection and Localization in Autonomous Robotics

A. Chella, I. Macaluso, Lorenzo Riano

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    10 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
    PublisherIEEE
    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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