动态生成模型，实时检测机器人故障根源。
Dynamic System Model Generation for Online Fault Detection and Diagnosis of Robotic Systems
- 运行时自动生成系统模型，无需预设参数
- 可适配多种相似软件架构的机器人
- 低开销且减少专家干预，适合工业部署
随着复杂机器人的快速发展，故障检测与诊断（FDD）日益困难。传统方法依赖预设模型和历史数据，难以应对系统动态变化。为此，本文提出一种运行时主动生成动态系统模型的新概念，利用该模型定位故障根因。目标是适用于具有相似软件设计的所有机器人系统，同时具备最小化计算开销，并降低对专家经验的依赖性，提升系统自主性与可扩展性。
原文摘要 · Abstract (English)
With the rapid development of more complex robots, Fault Detection and Diagnosis (FDD) becomes increasingly harder. Especially the need for predetermined models and historic data is problematic because they do not encompass the dynamic and fast-changing nature of such systems. To this end, we propose a concept that actively generates a dynamic system model at runtime and utilizes it to locate root causes. The goal is to be applicable to all kinds of robotic systems that share a similar software design. Additionally, it should exhibit minimal overhead and enhance independence from expert attention.
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