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Digital twin technology holds immense potential across various industries, including agriculture, aerospace, healthcare, and more. In the realm of autonomous electric vehicles, digital twin technology plays a crucial role in enabling unsupervised prognosis and control platforms, facilitating performance estimation and real-time monitoring. The primary objective of this research is to establish a seamless connection between the digital twin’s visualization software, represented by Unity, and the test bench’s loading motors, which simulate the road load on the propulsion drive system. This study also involves latency testing of various microcontrollers compatible with ROS2, specifically the ESP32-DevKitC-32E, Raspberry Pi Pico RP2040, and Teensy 4.0, to identify the fastest option for efficient message transmission. The results indicate that the Teensy 4.0 exhibited the highest message transmission frequency among the tested microcontrollers and was subsequently used to establish the connection between the scaled demonstrator and the visualization software of the digital twin.

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Establishing Visualization-to-Hardware Communication Through Middleware for Digital Twin with ROS-Compatible Microcontrollers Latency Tests

  • 会议论文

  • 发表日期：

    2026年

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  • Diana Belolipetskaja,
  • Anton Rassõlkin,
  • Hadi Ashraf Raja,
  • Pāvels Maksimkins,
  • Andrejs Stupāns

摘要

Digital twin technology holds immense potential across various industries, including agriculture, aerospace, healthcare, and more. In the realm of autonomous electric vehicles, digital twin technology plays a crucial role in enabling unsupervised prognosis and control platforms, facilitating performance estimation and real-time monitoring. The primary objective of this research is to establish a seamless connection between the digital twin’s visualization software, represented by Unity, and the test bench’s loading motors, which simulate the road load on the propulsion drive system. This study also involves latency testing of various microcontrollers compatible with ROS2, specifically the ESP32-DevKitC-32E, Raspberry Pi Pico RP2040, and Teensy 4.0, to identify the fastest option for efficient message transmission. The results indicate that the Teensy 4.0 exhibited the highest message transmission frequency among the tested microcontrollers and was subsequently used to establish the connection between the scaled demonstrator and the visualization software of the digital twin.