Augmented models for improving vision control of a mobile robot

Gert Lysgaard Andersen, Anders C. Christensen, Ole Ravn

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    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
    Publication date1994
    ISBN (Print)07-80-31872-2
    Publication statusPublished - 1994
    Event3rd IEEE Conference on Control Applications - Glasgow, United Kingdom
    Duration: 24 Aug 199426 Aug 1994
    Conference number: 3


    Conference3rd IEEE Conference on Control Applications
    CountryUnited Kingdom
    Internet address

    Bibliographical note

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    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.