数字孪生:网络物理生产系统中关键任务通信的网络配置

G. Szabó, Sándor Rácz, Norbert Reider, Hubertus A. Munz, József Peto
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引用次数: 13

摘要

数字孪生(DT)被广泛应用于各种工业领域,以优化物理资产、系统和制造过程的操作和维护。本文应用DT概念分析了网络对实际机器人控制的影响,其中实际机器人的DT运行在执行敏捷任务的复杂机器人单元中。我们提出了在Gazebo环境中实现可实现的DT的设计步骤。我们用真实的网络配置来评估我们提出的方法,以解决敏捷机器人工业自动化竞赛(ARIAC)[1]的完全模拟场景。评估结果表明,对于低延迟设置,仿真结果准确。对于高延迟设置,DT应该用于网络评估。研究还表明,机器人小区的最佳生产力性能需要5G超可靠低延迟通信(URLLC),而评估的公共LTE+网络也可以在有限的整体精度下使用。从[2]可以看到DT的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digital Twin: Network Provisioning of Mission Critical Communication in Cyber Physical Production Systems
Digital Twin (DT) is widely used in various industrial sectors to optimize the operations and maintenance of physical assets, system and manufacturing processes. This paper applies the DT concept on analyzing the effects of network on the control of a real robot where its DT runs in a complex robot cell executing agile tasks. We present the design steps applied to reach a realizable DT in the Gazebo environment. We evaluate our proposed method with real network configurations against a fully simulated scenario solving the Agile Robotics for Industrial Automation Competition (ARIAC) [1]. The evaluation results show that for low delay setups the simulation provides accurate results. For high delay setups the DT should be used for network assessment. It is also shown that 5G Ultra-Reliable Low-Latency Communication (URLLC) is required for the best productivity performance of the robot cell, while the evaluated public LTE+ network can also be used with limited overall accuracy. The DT in action can be seen on [2].
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