Design of an Integrated Visualization-Control Digital Twin and Middleware Architecture for Lightweight Robotic Arms

Junjie Xiong; Lei Ma; Xin Wang

doi:10.54097/rh3m5y71

Authors

Junjie Xiong
Lei Ma
Xin Wang

DOI:

https://doi.org/10.54097/rh3m5y71

Keywords:

Digital Twin, IoT Middleware, MQTT, Unity3D, Time-series Database

Abstract

With the in-depth advancement of the "Industry 4.0" strategy and the rapid development of intelligent manufacturing technologies, the digital twin, as a key technology bridging the physical world and the digital information world, has demonstrated tremendous application value in the fields of remote monitoring, fault diagnosis, and process simulation of industrial robots. However, traditional robotic arm control systems often suffer from issues such as a low degree of visualization, poor real-time performance in remote interactions, and a disconnection between the simulation environment and the physical entity. To address these challenges, this paper designs and implements an integrated visualization and control digital twin system for a five-axis robotic arm based on the MQTT protocol and a decoupled storage and access architecture. At the communication layer, the system discards the traditional point-to-point tightly coupled model and introduces an IoT distributed architecture based on the MQTT protocol. On the host computer side, a high-fidelity digital twin system is developed utilizing the Unity3D engine. By introducing a concurrent task queue and a packet boundary processing algorithm, high-precision bidirectional synchronization between virtual and physical entities, as well as automated operation planning, are achieved. To resolve the cloud concurrency blocking issue caused by massive high-frequency state data, this paper further designs a data persistence middleware based on Node.js asynchronous processes and the InfluxDB time-series database, realizing data stream cleaning, batch processing, and high-concurrency storage. Comprehensive performance tests demonstrate that the system can achieve bidirectional interaction between the digital twin and the physical entity with millisecond-level latency. Furthermore, the cloud middleware effectively reduces computational overhead, providing a lightweight solution with significant industrial application value for the digital and intelligent operation and maintenance of small and medium-sized robotic systems.

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