The authors present the application of artificial neural networks to the control of a mobile autonomous robot, which is acting in a totally unknown and-most importantly-dynamically changing environment. In particular, the employment of interacting 'simple', i.e. hand-designed, neural networks for navigation purposes is investigated as well as a variation of self-organizing maps for adaptive sensor calibration. We take a pragmatic point of view as the minimal condition imposed on the developed algorithms: that they do well on a real system acting in a real environment. Hence, the design of all of the implemented neural networks is clearly motivated by their applicability. In this context, special considerations are dedicated to ensure robustness, real-time capability and memory resourcefulness. In order to practically demonstrate the obtained results, the mini-robot Khepera is utilized as an experimentational platform, which is (due to its small size), a versatile tool for scientific investigation.


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    Titel :

    Artificial neural networks for autonomous robot control: reflective navigation and adaptive sensor calibration


    Beteiligte:
    Loffler, A. (Autor:in) / Klahold, J. (Autor:in) / Ruckert, U. (Autor:in)


    Erscheinungsdatum :

    1999


    Format / Umfang :

    6 Seiten, 15 Quellen




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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