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ROS-based architecture for fast digital twin development of smart manufacturing robotized systems

Author

Listed:
  • Carolina Saavedra Sueldo

    (INTELYMEC
    Universidad Nacional del Centro de la Provincia de Buenos Aires)

  • Ivo Perez Colo

    (INTELYMEC
    Universidad Nacional del Centro de la Provincia de Buenos Aires)

  • Mariano De Paula

    (INTELYMEC
    Universidad Nacional del Centro de la Provincia de Buenos Aires)

  • Sebastián A. Villar

    (INTELYMEC)

  • Gerardo G. Acosta

    (INTELYMEC)

Abstract

In the current era of Industry 4.0, smart manufacturing systems seek to achieve a high level of flexibility and efficiency. This can be achieved by means of incorporating a high degree of automation and autonomous robotized systems along with efficient decision-making systems capable to reconfigure the system tasks in real-time according to the external demands and perturbations. For the fast development of the digital twins of manufacturing plants that include some robotic devices, it is advantageous to use discrete-event simulators, for production process modeling, and the existing virtual environments of the robots and automatic devices. This work proposes the design and construction of software architecture capable of integrating discrete-event process simulators with the well-known Robot Operating System (ROS) allowing easily interchange information between the factory components for fast digital twin development of robotized manufacturing systems. In addition, our proposal allows for a straightforward integration between the digital twin with an autonomous decision-making system. The proposed ROS-based architecture is tested using different discrete-event simulators and the free distribution ROS Melodic. Finally, we present an instance of software architecture for a typical complex case study of manufacturing plants and demonstrate its easy integration with an autonomous decision-making system.

Suggested Citation

  • Carolina Saavedra Sueldo & Ivo Perez Colo & Mariano De Paula & Sebastián A. Villar & Gerardo G. Acosta, 2023. "ROS-based architecture for fast digital twin development of smart manufacturing robotized systems," Annals of Operations Research, Springer, vol. 322(1), pages 75-99, March.
    • Handle: RePEc:spr:annopr:v:322:y:2023:i:1:d:10.1007_s10479-022-04759-4
    DOI: 10.1007/s10479-022-04759-4
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    References listed on IDEAS

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    1. Volodymyr Mnih & Koray Kavukcuoglu & David Silver & Andrei A. Rusu & Joel Veness & Marc G. Bellemare & Alex Graves & Martin Riedmiller & Andreas K. Fidjeland & Georg Ostrovski & Stig Petersen & Charle, 2015. "Human-level control through deep reinforcement learning," Nature, Nature, vol. 518(7540), pages 529-533, February.
    2. George E. Monahan, 1982. "State of the Art---A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms," Management Science, INFORMS, vol. 28(1), pages 1-16, January.
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