Simulation of robotic tasks allows for cheap evaluation and process optimization, which can then be transferred to the physical system. To avoid discrepancies between physical execution and simulation, real-world process data can be fed back to the simulation environment, a concept referred to as a "Digital Twin". This requires the development of a software architecture, that supports Digital Twins for robot tasks.In this work, we propose a system where an operator can take apart a complex assembly, thus creating digitized assembly instructions. These instructions are then used to visually program the robot setup by blocks, which contain functionality ranging from point-to-point motions to high-level skills. These "Skillblocks"allow for a seamless transition between execution in the simulation environment and on the physical robot through interchangeable execution layers in the software architecture. The system also allows for feedback from a physical execution to be monitored in real-time and fed back to the simulation environment for processing.The aim of the system is to close the gap between digital and physical workcells when integrating robot solutions. This increases intuitiveness and allows for process monitoring and optimization through direct feedback to the digital model.


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    Titel :

    Towards Digital Twins for Industrial Assembly - Improving Robot Solutions by Intuitive User Guidance and Robot Programming


    Beteiligte:

    Erscheinungsdatum :

    2020-10-01


    Anmerkungen:

    Sørensen , L C , Mathiesen , S , Waspe , R & Schlette , C 2020 , Towards Digital Twins for Industrial Assembly - Improving Robot Solutions by Intuitive User Guidance and Robot Programming . in Proceedings - 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA . IEEE , I E E E International Conference on Emerging Technologies and Factory Automation. Proceedings , pp. 1480-1484 , 25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2020 , Vienna , Austria , 08/09/2020 . https://doi.org/10.1109/ETFA46521.2020.9212072



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    629




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