Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Roboterprogrammierung vereinfachen
    ( 2020)
    Guhl, J.
    ;
    Heimann, Oliver
    ;
    Krüger, Jörg
    Roboterprogrammierung ist trotz allen Weiterentwicklungen in der Steuerungstechnik und Mensch-Maschine-Interaktion immer noch ein kompliziertes Problem und dementsprechend kostspielig. Gerade in kleinen und mittelständischen Unternehmen stehen daher dem Robotereinsatz hohe Hürden gegenüber. Dieser Artikel befasst sich mit Möglichkeiten die Roboterprogrammierung - unter Zuhilfenahme von verschiedenen erweiterten Realitäten - zu vereinfachen und zu beschleunigen.
  • Publication
    Combining the Advantages of On- and Offline Industrial Robot Programming
    ( 2019)
    Guhl, Jan
    ;
    Nikoleizig, Sylvio
    ;
    Heimann, Oliver
    ;
    Hügle, Johannes
    ;
    Krüger, Jörg
    Classic off- and online programming approaches offer different advantages but cannot provide intuitive programming as it would be needed for frequent reconfiguration of industrial robotic cells and their programs. While a simulation and therewith a collision control can be used offline, highest precision can be achieved by using online teach-in. We propose a system that combines the advantages of both offline and online programming. By creating a programming framework that is independent of in- and output devices we allow the use of augmented as well as virtual reality. Thus, enabling the user to choose for a programming technique that best suits his needs during different stages of programming. Bringing together both methods allows us to not only drastically reduce programming time but simultaneously increase intuitiveness of human robot interaction.
  • Publication
    Affordance Based Approach to Automatic Program Generation for Industrial Robots in Manufacturing
    ( 2018)
    Heimann, Oliver
    ;
    Krüger, Jörg
    Due to the increasing demand for flexible and low-cost production, manufacturing solutions involving human robot interaction have become much sought-after. Robotic manufacturers meet the demand with a rising number of low cost robots specifically designed around safety and usability. However, the programming is still based on a tool centric teach-in. This paper discusses an affordance based approach for process programming in industrial manufacturing. Using low level feature detection and a consecutive evaluation, a fast programming method for industrial applications is presented. The paper presents the concept and a prototypic implementation for a welding process. Using the affordance detection, the system is able to identify relevant seams based on an image of the work space. The identified seams are then presented to the user for review with the means of augmented reality. Lastly, the system derives a welding program based on the detected seams. First experiments show promising results concerning programming speed and path accuracy for different work piece shapes and task definitions. Finally, based on the experience gained with the prototype, the outlook discusses the possibilities and further fields for future work.