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On the Diagnosability of Actions Performed by Contemporary Robotic Systems

  • When a robotic agent experiences a failure while acting in the world, it should be possible to discover why that failure has occurred, namely to diagnose the failure. In this paper, we argue that the diagnosability of robot actions, at least in a classical sense, is a feature that cannot be taken for granted since it strongly depends on the underlying action representation. We specifically define criteria that determine the diagnosability of robot actions. The diagnosability question is then analysed in the context of a handle manipulation action, such that we discuss two different representations of the action – a composite policy with a learned success model for the action parameters, and a neural network-based monolithic policy – both of which exist on different sides of the diagnosability spectrum. Through this comparison, we conclude that composite actions are more suited to explicit diagnosis, but representations with less prior knowledge are more flexible. This suggests that model learning may provide balance between flexibility and diagnosability; however, data-driven diagnosis methods also need to be enhanced in order to deal with the complexity of modern robots.

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Metadaten
Document Type:Conference Object
Language:English
Author:Alex MitrevskiORCiD, Ahmed Faisal Abdelrahman, Anirudh Narasimamurthy, Paul G. Plöger
Parent Title (English):31th International Workshop on Principles of Diagnosis (DX'20)
URL:http://dx-2020.org/papers/DX-2020_paper_6.pdf
Date of first publication:2020/09/26
Tag:robot action diagnosability; robot execution failures; robotics
Departments, institutes and facilities:Fachbereich Informatik
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2020/10/06