用变分自编码器构建智能数字孪生，实现机器人热状态的无监督预测与自我预警。
Deep Generative and Discriminative Digital Twin endowed with Variational Autoencoder for Unsupervised Predictive Thermal Condition Monitoring of Physical Robots in Industry 6.0 and Society 6.0
- 基于变分自编码器构建数字孪生，通过重构误差衡量热负荷难易度。
- 可提前预测电机过热风险，支持无人干预下的热安全运行。
- 适合工业6.0和人本社会中需高可靠性的协作机器人场景。
在工业4.0中，机器人被广泛用于提升效率；在工业5.0中，它们则为劳动力提供协同与可持续支持。随着抗脆弱制造和以人为本的社会任务对韧性、鲁棒性和安全性要求提高，机器人需自主预判并应对因电机过热导致的热饱和与灼伤，以保障人身安全与设备可用性。传统做法是热饱和时强制停机，这会降低工厂产能并影响社会舒适度，且冷却策略难以在机器人购入后实施。本文提出一种融合生成式AI（变分自编码器）的智能数字孪生系统，用于管理热异常并生成安全状态。通过变分自编码器的重构误差定义热难度指标，机器人可据此预测、预判并共享运动轨迹的热可行性，满足工业6.0与社会6.0新兴应用的需求，实现自主维持性能、延长寿命且无需人工干预。
原文摘要 · Abstract (English)
Robots are unrelentingly used to achieve operational efficiency in Industry 4.0 along with symbiotic and sustainable assistance for the work-force in Industry 5.0. As resilience, robustness, and well-being are required in anti-fragile manufacturing and human-centric societal tasks, an autonomous anticipation and adaption to thermal saturation and burns due to motors overheating become instrumental for human safety and robot availability. Robots are thereby expected to self-sustain their performance and deliver user experience, in addition to communicating their capability to other agents in advance to ensure fully automated thermally feasible tasks, and prolong their lifetime without human intervention. However, the traditional robot shutdown, when facing an imminent thermal saturation, inhibits productivity in factories and comfort in the society, while cooling strategies are hard to implement after the robot acquisition. In this work, smart digital twins endowed with generative AI, i.e., variational autoencoders, are leveraged to manage thermally anomalous and generate uncritical robot states. The notion of thermal difficulty is derived from the reconstruction error of variational autoencoders. A robot can use this score to predict, anticipate, and share the thermal feasibility of desired motion profiles to meet requirements from emerging applications in Industry 6.0 and Society 6.0.
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