Mobile robots play a key role in a number of different automation tasks. Robots capable of omnidirectional motion allow for a particularly very flexible operation. They are able to move in every direction, regardless of their orientation. A common task for industrial mobile robots is trajectory tracking. These trajectories often are periodic, e. g., if the same path is followed repeatedly through a large warehouse or at an assembly line. In the contribution, it is shown how data-based techniques can be used to tailor a motion model to a specific re-occurring reference, resulting in highly accurate tracking. The results of this work are finally validated in real-world hardware experiments. This novel contribution builds upon preliminary work but, for the first time, includes an adaptive component for high accuracy tracking of periodic references as well as a general approach to generating periodic input and state references based on a dynamic model of a robot.


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    Titel :

    High Accuracy Data-Based Trajectory Tracking of an Omnidirectional Mobile Robot


    Weitere Titelangaben:

    Mechan. Machine Science


    Beteiligte:
    Müller, Andreas (Herausgeber:in) / Brandstötter, Mathias (Herausgeber:in) / Eschmann, Hannes (Autor:in) / Ebel, Henrik (Autor:in) / Eberhard, Peter (Autor:in)

    Kongress:

    International Conference on Robotics in Alpe-Adria Danube Region ; 2022 ; Klagenfurt, Austria June 08, 2022 - June 10, 2022



    Erscheinungsdatum :

    2022-04-23


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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