We investigate the shot-aiming problem in Pinball and design a model predictive controller to take shots toward targets with minimal trajectory error using a k-Nearest Neighbor regression-based flip function. A flip function maps the ball's state to its launch trajectory parameters. The k-Nearest Neighbor regression algorithm is applied to reduce the number of calibration shots required to estimate the flip function accurately. The controller is developed for a simulator built with Visual Pinball. The test results from this controller are compared to a controller built with a polynomial flip function. The experiments showed that the controller could accurately aim shots toward targets with minor trajectory errors after a few initialization shots.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Real-Time Model Predictive Control for Shot Aiming in Pinball Using k-NN Regression


    Beteiligte:


    Erscheinungsdatum :

    28.08.2023


    Format / Umfang :

    1725927 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Predictive Algorithm For Aiming An Antenna

    Gawronski, Wodek K. | NTRS | 1993



    Output aiming control

    Meerkov, S.M. / Runolfsson, T. | Tema Archiv | 1987


    Model predictive flight control using adaptive support vector regression

    Shin, Jongho / Kim, H. Jin / Park, Sewook et al. | Tema Archiv | 2010