Augmented models for improving vision control of a mobile robot

Gert Lysgaard Andersen, Anders C. Christensen, Ole Ravn

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    Abstract

    This paper describes the modelling phases for the design of a path tracking vision controller for a three wheeled mobile robot. It is shown that, by including the dynamic characteristics of vision and encoder sensors and implementing the total system in one multivariable control loop, one can obtain good performance even when using standard low cost equipment and a comparatively low sampling rate. The plant model is a compound of kinematic, dynamic and sensor submodels, all integrated into a discrete state space representation. An intelligent strategy is applied for the vision sensor, including the start up, normal operation, exception handling and shut down phases. Laboratory experiments show the validity of the approach using standard Kalman filter/LQR control design
    Original languageEnglish
    Title of host publicationProceedings of the Third IEEE Conference on Control Applications
    VolumeVolume 1
    PublisherIEEE
    Publication date1994
    Pages53-58
    ISBN (Print)07-80-31872-2
    DOIs
    Publication statusPublished - 1994
    Event3rd IEEE Conference on Control Applications - Glasgow, United Kingdom
    Duration: 24 Aug 199426 Aug 1994
    Conference number: 3
    http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=3047

    Conference

    Conference3rd IEEE Conference on Control Applications
    Number3
    CountryUnited Kingdom
    CityGlasgow
    Period24/08/199426/08/1994
    Internet address

    Bibliographical note

    Copyright 1994 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

    Cite this

    Andersen, G. L., Christensen, A. C., & Ravn, O. (1994). Augmented models for improving vision control of a mobile robot. In Proceedings of the Third IEEE Conference on Control Applications (Vol. Volume 1, pp. 53-58). IEEE. https://doi.org/10.1109/CCA.1994.381270