Beyond conventional automated tasks, autonomous robot capabilities aside human cognitive skills are gaining importance in industrial applications. Although machine learning is a major enabler of autonomous robots, system adaptation remains challenging and time-consuming. The objective of this research work is to propose and evaluate an augmented virtuality-based input demonstration refinement method improving hybrid manipulation learning for industrial bin picking. To this end, deep reinforcement and imitation learning are combined to shorten required adaptation timespans to new components and changing scenarios. The method covers initial learning and dataset tuning during ramp-up as well as fault intervention and dataset refinement. For evaluation standard industrial components and systems serve within a real-world experimental bin picking setup utilizing an articulated robot. As part of the quantitative evaluation, the method is benchmarked against conventional learning methods. As a result, required annotation efforts for successful object grasping are reduced. Thereby, final grasping success rates are increased. Implementation samples are available on: https://github.com/FAU-FAPS/hybrid_manipulationlearning_unity3dros


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Augmented Virtuality Input Demonstration Refinement Improving Hybrid Manipulation Learning for Bin Picking


    Weitere Titelangaben:

    Lect.Notes Mechanical Engineering


    Beteiligte:
    Kim, Kyoung-Yun (Herausgeber:in) / Monplaisir, Leslie (Herausgeber:in) / Rickli, Jeremy (Herausgeber:in) / Blank, Andreas (Autor:in) / Zikeli, Lukas (Autor:in) / Reitelshöfer, Sebastian (Autor:in) / Karlidag, Engin (Autor:in) / Franke, Jörg (Autor:in)

    Kongress:

    International Conference on Flexible Automation and Intelligent Manufacturing ; 2022 ; Detroit, MI, USA June 19, 2022 - June 23, 2022



    Erscheinungsdatum :

    13.10.2022


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






    An augmented virtuality teleoperation system

    Prexl, Maximilian | TIBKAT | 2021


    Review of augmented virtuality technology in virtual reality

    Aimin, H. / Bing, H. / Qinping, Z. | British Library Online Contents | 2003


    Technology - Protoscar, concrete virtuality

    Cornil, Daniele | Online Contents | 2000


    AutoSimAR: In-Vehicle Cross-Virtuality Transitions between Planar Displays and 3D Augmented Reality Spaces

    Riegler, Andreas / Anthes, Christoph / Holzmann, Clemens et al. | DataCite | 2021