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Abstract：
Since 2015, there has been an increase in articles on anomaly detection in robotic systems, reflecting its growing importance in improving the robustness and reliability of the increasingly utilized autonomous robots. This review paper investigates the literature on the detection of anomalies in Autonomous Robotic Missions (ARMs). It reveals different perspectives on anomaly and juxtaposition to fault detection. To reach a consensus, we infer a unified understanding of anomalies that encapsulate their various characteristics observed in ARMs and propose a classification of anomalies in terms of spatial, temporal, and spatiotemporal elements based on their fundamental features. Further, the paper discusses the implications of the proposed unified understanding and classification in ARMs and provides future directions. We envisage a study surrounding the specific use of the term anomaly, and methods for their detection could contribute to and accelerate the research and development of a universal anomaly detection system for ARMs.
摘要：
自2015年以来，有关机器人系统异常检测的文章有所增加，反映了其在提高越来越多地使用的自主机器人的鲁棒性和可靠性方面的重要性。本文研究了有关自主机器人任务（ARM）异常检测的文献。它揭示了异常和并置与故障检测的不同观点。达成共识,我们推断了对异常的统一理解，这些异常包含了在ARM中观察到的各种特征，并提出了在空间上对异常的分类，temporal,和基于其基本特征的时空要素。Further,本文讨论了拟议的统一理解和分类在ARM中的意义，并提供了未来的方向。我们设想围绕术语异常的特定用法进行研究，以及它们的检测方法可以促进和加速ARM通用异常检测系统的研究和开发。
