In recent years, with the deepening integration of digital twins (DT) and the Industrial Internet of Things (IIoT), solutions based on digital twins have been widely applied in IIoT scenarios. However, most existing solutions tend to overlook the latency issue during the interaction between mobile devices, such as industrial mobile robots (IMR), and their DTs while in motion. Excessive interaction latency can directly impair the real-time response capability and decision accuracy of industrial mobile robots, and in severe cases, it may lead to the failure of intricate industrial tasks. In order to solve the above problems, we propose a digital twin dynamic migration method for industrial mobile robots. Firstly, we design and implement a STGCN-Transformer-based movement trajectory prediction method for IMR to predict the future movement trajectory of IMR and pre-migrate the DT of IMR to all intelligent gateways (IG) within the prediction range. Then, we design and implement a Proximal Policy Optimization-based DT migration time determination method for IMR and obtain the migration timing of DT under the premise of balancing the DT migration overhead, the load of the IG where the DT is deployed, the load of the IG where the DT is connected, and the communication delay between the IMR and the IG where the DT is deployed. Next, the DT of the IMR is migrated based on the IMR’s anticipated trajectory and optimal times for migration, with the objective of minimizing the interaction latency between the IMR and its DT. Finally, we conduct simulation experiments on the proposed method. Through theoretical and simulation experiments, it has been proven that the proposed method can effectively ensure the dynamic interaction delay between the IMR and its DT during the moving process, thereby enhancing the real-time responsiveness and decision precision of the IMR.

中文翻译：

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一种面向工业移动机器人的数字孪生动态迁移方法


近年来，随着数字孪生 （DT） 与工业物联网 （IIoT） 的深度融合，基于数字孪生的解决方案在 IIoT 场景中得到了广泛的应用。然而，大多数现有解决方案往往忽略了移动设备（如工业移动机器人 （IMR））与其移动中的 DT 之间交互时的延迟问题。过长的交互延迟会直接损害工业移动机器人的实时响应能力和决策准确性，严重时可能导致错综复杂的工业任务失败。为了解决上述问题，我们提出了一种工业移动机器人数字孪生动态迁移方法。首先，我们设计并实现了基于 STGCN-Transformer 的 IMR 运动轨迹预测方法，以预测 IMR 的未来运动轨迹，并将 IMR 的 DT 预迁移到预测范围内的所有智能网关 （IG）。然后，我们设计并实现了一种基于 Proximal Policy Optimization 的 IMR DT 迁移时间确定方法，并在平衡 DT 迁移开销、DT 部署的 IG 负载、DT 连接的 IG 负载以及 IMR 与 DT 部署的 IG 之间的通信延迟的前提下，获取 DT 的迁移时序。接下来，根据 IMR 的预期轨迹和最佳迁移时间迁移 IMR 的 DT，目的是最大限度地减少 IMR 与其 DT 之间的交互延迟。最后，我们对所提出的方法进行了仿真实验。 通过理论和仿真实验证明，所提方法能够有效保证IMR在移动过程中与其DT之间的动态交互延迟，从而提高IMR的实时响应性和决策精度。