Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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  • Publication
    Universal identification and control of industrial manufacturing equipment as a service
    ( 2021)
    Tessaro, V.
    ;
    Vick, A.
    ;
    Krüger, J.
    This paper presents a universal approach of identification and closed-loop control of manufacturing equipment, de- livered through web services using Open Platform Communications United Architecture (OPC UA). Rapid prototyping as well as retrofitting and digitization of legacy systems often need design and application of closed-loop controllers. The analysis and modelling for systems such as energy-conversion or material transport devices is labour-intensive and needs process understanding. Current identification and control toolboxes require systematic preparation of input/output data, modification and tuning of the derived models, also proper design of classic PID controllers. An on-demand service paradigm is applied to allow identification and control with direct access to the controlled system over a network connection. The identified parameters are used to adapt a model predictive controller (MPC), which stabilizes the system and drives trajectories to different operating points. To evaluate the performance of the controllers in terms of stability, accuracy, and time response, several target trajectories and disturbances (signal noise, external physical disturbances, latency in communication) were investigated. The identification service was used to model the linear dynamics of a 6-DOF industrial robot and a laboratory-scale waterworks containing two separately controllable pumps. The robot's axes and the waterworks' pumps were successfully controlled with current set-points by using their respective identified state-space models. Simulation and laboratory experiments show promising results for the control of diverse systems with varying time-constants, and imply broad applicability. As a major achievement, this approach enables to efficiently implement system identification and model predictive control in manufacturing.
  • Publication
    DRL-basierte Navigationsansätze in der industriellen Robotik
    ( 2021)
    Kästner, L.
    ;
    Lambrecht, J.
    ;
    Vick, A.
    ;
    Krüger, J.
    Mobile Roboter sind in verschiedenen Bereichen der Industrie zu wichtigen Werkzeugen geworden, insbesondere in der Logistik. Die sichere Navigation in hochdynamischen Umgebungen stellt jedoch weiterhin eine große Herausforderung für klassische Pfadplanungsansätze dar. Deep Reinforcement Learning (DRL) hat sich als alternative Planungsmethode herauskristallisiert, um allzu konservative Ansätze zu ersetzen und verspricht eine effizientere und flexiblere Navigation. Diese Ansätze sind jedoch aufgrund ihrer Anfälligkeit für lokale Minima und das Mangeln eines Langzeitgedächtnisses nicht für die Langstreckennavigation geeignet, was eine breite Integration in industrielle Anwendungen der mobilen Robotik behindert. Dieser Beitrag stellt einen Ansatz für die Integration von DRL-basierter Navigation in existierende Navigationsansätze von industrieller mobiler Robotik vor.
  • Publication
    Resilienz durch Redundanz. Cloud-und Edge-basierte Echtzeitsteuerung von autonomen mobilen Robotern
    ( 2021)
    Nouruzi-Pur, J.
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    Lambrecht, J.
    ;
    Nguyen, T.D.
    ;
    Vick, A.
    ;
    Krüger, J.
    Die Auslagerung von Algorithmen auf Edge- und Cloud- umgebungen nach dem Software-as-a-Service-Paradigma bringt viele Vorteile für autonome mobile Roboter mit sich. Es kann jedoch nicht immer garantiert werden, dass die QoS-Anforderungen der ausgelagerten echtzeitkritischen Funktionen erfüllt sind. Das Bereitstellen von redundanten Kommunikationsmöglichkeiten und Berechnungsknoten sowie robotergesteuertes Umschalten ermöglichen Echtzeitfähigkeit innerhalb dieser unsicheren Infrastrukturen.
  • Publication
    Reale Daten für Simulationen im digitalen Zwilling - Untersuchung zur Aufnahme von Profinet-Daten und deren Wiedergabe in komplexen Simulationsumgebungen
    ( 2019)
    Chemnitz, M.
    ;
    Heimann, O.
    ;
    Vick, A.
    Powerful engineering tools are required to keep modern production systems manageable. Siemens DI FA and the Fraunhofer IPK present a novel tool for root cause analysis within complex manufacturing systems. The solution combines a CAx plant model with control data recorded from the field bus. This creates a comprehensive digital twin, allowing to analyse past machine behavior with bus clock resolution.
  • Publication
    Reale Daten für Simulationen im digitalen Zwilling
    ( 2019)
    Chemnitz, Moritz
    ;
    Heimann, Oliver
    ;
    Vick, A.
    Die hohen Anforderungen an moderne Fertigungssysteme erfordern leistungsfähige Engineering-Lösungen. Wie man die Identifikation von Fehlerursachen in komplexen Anlagen erleichtert, wurde in einer Machbarkeitsstudie des Fraunhofer IPK im Auftrag von Siemens DI FA untersucht. In der vorgestellten Lösung werden die Daten der Anlage auf Feldbusebene erfasst und in den digitalen Zwilling eingespeist. So kann das Verhalten der Komponenten taktgenau nachvollzogen werden. Dies erlaubt einen tiefen Einblick in das System und unterstützt so bei der Fehlerbehebung.
  • Publication
    Maximization of operational workspace of a mobile manipulator system
    ( 2018)
    Kalidindi, V.V.
    ;
    Vick, A.
    ;
    Krüger, J.
    This paper puts forward a proposition of designing manipulator setup on a mobile platform so as to enhance the Operational Workspace range of a given Mobile-Manipulator system, by introducing the concept of Installation angle. This concept is theoretically tested on a Mobile-manipulator system built from the chosen robots, for the given operational parameters. As a part of this testing, Manipulator workspace has been expressed and approximated in terms of its enclosure volume for quantitative comparability.
  • Publication
    Motion planning with motion primitives for industrial bin picking
    ( 2018)
    Vonasek, V.
    ;
    Vick, A.
    ;
    Saska, M.
    In the bin picking problem, the task is to automatically unload objects from a container using a robotic manipulator. The task is often approached by organizing the objects into a predictable pattern, e.g., a workpiece carrier, in order to simplify all integral subtasks like object recognition, motion planning and grasping. In such a case, motion planning can even be solved offline as it is ensured that the objects are always at the same positions at known times. However, there is a growing demand for non-structured bin picking, where the objects can be placed randomly in the bins. This arises from recent trends of transforming classical factories into smart production facilities allowing small lot sizes at the efficiency of mass production. The demand for fast and highly flexible handling and manipulation abilities of industrial robots requires to solve all the bin picking methods, including motion planning, online. In this paper, we propose a novel technique for fast sampling-based motion planning of robotic manipulators using motion primitives. Motion primitives are short trajectories that boost search of the configuration space and consequently speed up the planning phase. The proposed work has been verified in a simulation and on a prototype of a bin picking system.
  • Publication
    Model predictive control as a service - concept and architecture for use in cloud-based robot control
    ( 2016)
    Vick, A.
    ;
    Guhl, J.
    ;
    Krüger, J.
    This paper presents the concept and architecture of a model predictive feedback control system to be used for compensating communication delays in networked industrial robot control. This approach follows the ideas given by the paradigms of Industrie 4.0 that demand for highly networked production devices and functions on different machine layers and IT hierarchy levels. We push the concept of fully outsourced control systems to a point, where even real-time critical feedback processes are driven from cloud-based services over uncertain public networks.
  • Publication
    Cloudbasierte Industrierobotersteuerungen
    ( 2016)
    Guhl, J.
    ;
    Vick, A.
    ;
    Nguyen, T.
    ;
    Wassermann, J.
    ;
    Krüger, J.
  • Publication
    Cloud- und dienstebasierte Produktionsplattformen
    ( 2016)
    Vick, A.
    ;
    Krüger, J.
    Nach dem Start des Zukunftsprojekts Industrie 4.0 gibt es viele verschiedene Ansätze zur Vernetzung von industriellen Anlagen, Datenverarbeitungssystemen und dem Unternehmensmanagement. In diesem Beitrag sind die grundsätzlichen Potenziale und technischen Anforderungen für eine cloudbasierte Produktion zusammengefasst. Dabei werden mögliche Plattformen, die dienstebasierte Modularisierung der Produktion bis hin zur Virtualisierung konkreter Steuerungsaufgaben beleuchtet.