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A Framework for Robust and Incremental Self-Localization

Matjaž Jogan and Matej Artač and Danijel Skočaj and Aleš Leonardis (2003) A Framework for Robust and Incremental Self-Localization. [Dataset] (Unpublished)

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    In this contribution we present a framework for an embodied robotic system that is capable of appearance-based self-localization. Specifically, we concentrate on the issues of robustness, flexibility, and scalability of the system. The framework presented is based on a panoramic eigenspace model of the environment. Its main feature is that it allows for simultaneous localization and map building using an incremental learning algorithm. Further, both the learning and the training processes are designed in a way to achieve robustness and adaptability to changes in the environment.

    Item Type: Dataset
    Keywords: autonomous systems, robotics, self-localization, cognitive vision, eigenspace methods
    Language of Content: English
    Related URLs:
    URLURL Type
    http://www.cobiss.si/scripts/cobiss?command=search&base=50070&select=(id=3575380)Alternative location
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=50070&select=(ID=)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Divisions: Faculty of Computer and Information Science > Computer Vision Laboratory
    Item ID: 83
    Date Deposited: 22 May 2003
    Last Modified: 11 Dec 2013 10:02
    URI: http://eprints.fri.uni-lj.si/id/eprint/83

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