In recent times, learning by demonstration has seen tremendous progress in robotic assembly operations. One of the most prominent trajectory-level task models applied is Dynamic Movement Primitives (DMP). However, it lacks the ability to tackle complex operations as often encountered in industrial assembly. Augmenting low-level models with a high-level framework in which different movement segments are deliberately parameterised is considered promising for such scenarios. This paper investigates the combination of trajectory-level DMPs with Methods-Time Measurement (MTM). We demonstrate how the MTM-1 system is utilised to establish distinguished DMP models for five of its basic elements, paving the way to benefitting from the sophisticated MTM system. The evaluation of the framework is conducted on a generic pick and place operation. Compared to a one-model-fits-all DMP approach for the whole task, the proposed method shows the advantage of appropriate temporal scaling, accuracy levelling and force consideration at adequate times.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Towards Learning by Demonstration for Industrial Assembly Tasks


    Beteiligte:
    Schüppstuhl, Thorsten (Herausgeber:in) / Tracht, Kirsten (Herausgeber:in) / Fleischer, Jürgen (Herausgeber:in) / Hernandez Moreno, Victor (Autor:in) / Carmichael, Marc G. (Autor:in) / Deuse, Jochen (Autor:in)

    Kongress:

    MHI Colloquium ; 2022 ; Karlsruhe, Germany July 20, 2022 - July 21, 2022



    Erscheinungsdatum :

    11.07.2023


    Format / Umfang :

    11 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    Demonstration Shaped Reward Machine for Robot Assembly Reinforcement Learning Tasks

    Xiao, Ruihong / Zhan, Hong / Jiang, Yiming et al. | Springer Verlag | 2023


    Demonstration Shaped Reward Machine for Robot Assembly Reinforcement Learning Tasks

    Xiao, Ruihong / Zhan, Hong / Jiang, Yiming et al. | TIBKAT | 2023




    Learning of Exception Strategies in Assembly Tasks

    Nemec, Bojan / Simonič, Mihael / Ude, Aleš | BASE | 2020

    Freier Zugriff