详细信息
- 来源站点
- ArXiv CS.AI
- 作者
- Karim Othman, Jonas Petersen, Matei Ignuta-Ciuncanu, Camilla Mazzoleni, Federico Martelli, Alessandro Lombardi, Riccardo Maggioni, Philipp Petersen
- 文章类型
- NEWS
- 语言
- en
- 发布日期
- 2026-05-26
摘要
arXiv:2605.09081v3 Announce Type: replace-cross Abstract: We introduce the first universal pretraining corpus for industrial time-series data: FactoryNet. 51M datapoints across 23k end-to-end task executions (13.3k real, 9.8k synthetic) on six embodiments, unified by a shared schema that enables robust zero-shot cross-embodiment transfer and highly parameter-efficient anomaly detection. We introduce a novel schema: Setpoint, Effort, Feedback, Context (S-E-F-C) underlying the whole pipeline that maps any actuated system into a common representational frame. The corpus spans 27 annotated anomaly types alongside healthy baselines and counterfactual pairs across robotic manipulation and machining domains.