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  • 1.
    Salman, Chaudhary Awais
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. ABB AB, Västers, Sweden.
    Struhar, Vaclav
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Behnam, Moris
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fogification of industrial robotic systems: Research challenges2019In: IoT-Fog 2019 - Proceedings of the 2019 Workshop on Fog Computing and the IoT, Association for Computing Machinery, Inc , 2019, p. 41-45Conference paper (Refereed)
    Abstract [en]

    To meet the demands of future automation systems, the architecture of traditional control systems such as the industrial robotic systems needs to evolve and new architectural paradigms need to be investigated. While cloud-based platforms provide services such as computational resources on demand, they do not address the requirements of real-time performance expected by control applications. Fog computing is a promising new architectural paradigm that complements the cloud-based platform by addressing its limitations. In this paper, we analyse the existing robot system architecture and propose a fog-based solution for industrial robotic systems that addresses the needs of future automation systems. We also propose the use of Time-Sensitive Networking (TSN) services for real-time communication and OPC-UA for information modelling within this architecture. Additionally, we discuss the main research challenges associated with the proposed architecture.

  • 2.
    Struhar, Vaclav
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ashjaei, Seyed Mohammad Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Behnam, Moris
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Craciunas, Silviu
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    DART: Dynamic Bandwidth Distribution Framework for Virtualized Software Defined Networks2019In: IEEE 45th Annual Conference of the Industrial Electronics Society IECON'19, 2019Conference paper (Refereed)
  • 3.
    Struhar, Vaclav
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Behnam, Moris
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Work-in-Progress: Fog Computing for Adaptive Human-Robot Collaboration2018In: International Conference on Embedded Software 2018 EMSOFT2018, 2018, article id 8537213Conference paper (Refereed)
    Abstract [en]

    Fog computing is an emerging technology that enables the design of novel time sensitive industrial applications. This new computing paradigm also opens several new research challenges in different scientific domains, ranging from computer architectures to networks, from robotics to real-time systems. In this paper, we present a use case in the human-robot collaboration domain, and we identify some of the most relevant research challenges.

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