Online Unsupervised Cumulative Learning For Life-Long Robot Operation

Y Gatsoulis, C Burbridge, TM McGinnity

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

    7 Citations (Scopus)
    5 Downloads (Pure)

    Abstract

    The effective life-long operation of service robots and assistive companions depends on the robust ability of the system to learn cumulatively and in an unsupervised manner. For a cumulative learning robot there are particular characteristics that the system should have, such as being able to detect new perceptions, being able to learn online and without supervision, expand when required, etc. Bag-of-Words is a generic and compact representation of visual perceptions which has commonly and successfully been used in object recognition problems. However in its original form, it is unable to operate online and expand its vocabulary when required.This paper describes a novel method for cumulative unsupervised learning of objects by visual inspection, using an online and expanding when required Bag-of-Words. We present a set of experiments with a real-world robot, which cumulatively learns a series of objects. The results show that the system is able to learn cumulatively and recall correctly the objects it was trained on.
    Original languageEnglish
    Title of host publicationUnknown Host Publication
    PublisherIEEE
    Pages2486-2490
    Number of pages6
    Publication statusPublished - 7 Dec 2011
    Event2011 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO'2011 - Phuket, Thailand
    Duration: 7 Dec 2011 → …

    Conference

    Conference2011 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO'2011
    Period7/12/11 → …

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  • Cite this

    Gatsoulis, Y., Burbridge, C., & McGinnity, TM. (2011). Online Unsupervised Cumulative Learning For Life-Long Robot Operation. In Unknown Host Publication (pp. 2486-2490). IEEE.