We present a neural-network method to recalibrate automatically a commercial robot after undergoing wear or damage, which works on top of the nominal inverse kinematics embedded in its controller. Our starting point has been the work of Ritter et al. (1989, 1992) on the use of extended self-organizing maps to learn the whole inverse kinematics mapping from scratch. Besides adapting their approach to learning only the deviations from the nominal kinematics, we have introduced several modifications to improve the cooperation between neurons. These modifications not only speed up learning by two orders of magnitude, but also produce some desirable side effects, like parameter stability. After extensive experimentation through simulation, the recalibration system has been installed in the REIS robot included in the space-station mock-up at Daimler-Benz Aerospace. Tests performed in this set-up have been constrained by the need to preserve robot integrity, but the results have been concordant with those predicted through simulation.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Self-calibration of a space robot


    Additional title:

    Wie ein mobiler Roboter in einer Weltraumstation sich nach einer Kollision mittels eines neuronalen Netzes selber eicht


    Contributors:

    Published in:

    Publication date :

    1997


    Size :

    13 Seiten, 12 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




    Self-calibration of a space robot

    Ruiz de Angulo, Vicente / Torras, Carme | BASE | 1997

    Free access

    Self-calibration guide wheel of fire-fighting robot

    XU YUN / KONG CHANGJIAN / ZHANG XINXIA et al. | European Patent Office | 2021

    Free access


    Simultaneous localization and odometry self calibration for mobile robot

    Martinelli, A. | British Library Online Contents | 2007


    Modularized self-reconfiguration space software robot

    WU LIGANG / YAO YURAN / CHEN WEILIANG et al. | European Patent Office | 2023

    Free access