Digital Twin (DT) technology is transforming robotics by enabling synchronization, data consistency and precise servo control. In the context of Product Lifecycle Management, this study proposes a DT framework to achieve integration and synchronization between a physical robotic system and its virtual counterpart through bi-directional data exchange. Specifically, we develop a DT-based control and monitoring system for the Tinkerkit Braccio robotic arm, leveraging the 3DEXPERIENCE platform and Dymola while ensuring command and feedback synchronization via an Arduino board. By integrating physics-based and data-driven models to ensure synchronization between the physical robot and its virtual counterpart, the research addresses mechanical modelling, robot simulation, control architecture design and refinement of Functional Mockup Units (FMU). The integration of logical references and a robust control architecture align with PLM strategies of promoting robust operations and collaboration for smarter and more efficient robotic systems.

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A Digital Twin Framework for Enhanced Robot Control Through Data Exchange Protocols

  • Hadria Nada,
  • Valeria Croce,
  • Philippe Véron

摘要

Digital Twin (DT) technology is transforming robotics by enabling synchronization, data consistency and precise servo control. In the context of Product Lifecycle Management, this study proposes a DT framework to achieve integration and synchronization between a physical robotic system and its virtual counterpart through bi-directional data exchange. Specifically, we develop a DT-based control and monitoring system for the Tinkerkit Braccio robotic arm, leveraging the 3DEXPERIENCE platform and Dymola while ensuring command and feedback synchronization via an Arduino board. By integrating physics-based and data-driven models to ensure synchronization between the physical robot and its virtual counterpart, the research addresses mechanical modelling, robot simulation, control architecture design and refinement of Functional Mockup Units (FMU). The integration of logical references and a robust control architecture align with PLM strategies of promoting robust operations and collaboration for smarter and more efficient robotic systems.