SMOF - A Safety MOnitoring Framework for Autonomous Systems

Abstract : Safety critical systems with decisional abilities, such as autonomous robots, are about to enter our everyday life. Nevertheless, confidence in their behavior is still limited, particularly regarding safety. Considering the variety of hazards that can affect these systems, many techniques might be used to increase their safety. Among them, active safety monitors are a means to maintain the system safety in spite of faults or adverse situations. The specification of the safety rules implemented in such devices is of crucial importance, but has been hardly explored so far. In this paper, we propose a complete framework for the generation of these safety rules based on the concept of safety margin. The approach starts from a hazard analysis, and uses formal verification techniques to automatically synthesize the safety rules. It has been successfully applied to an industrial use case, a mobile manipulator robot for co-working.
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IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE, 2018, 48 (5), pp.702-715. 〈10.1109/TSMC.2016.2633291〉
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https://hal.archives-ouvertes.fr/hal-01394139
Contributeur : Jérémie Guiochet <>
Soumis le : lundi 23 janvier 2017 - 16:59:40
Dernière modification le : mardi 4 décembre 2018 - 01:22:16
Document(s) archivé(s) le : lundi 24 avril 2017 - 12:05:02

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Mathilde Machin, Jérémie Guiochet, Hélène Waeselynck, Jean-Paul Blanquart, Matthieu Roy, et al.. SMOF - A Safety MOnitoring Framework for Autonomous Systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE, 2018, 48 (5), pp.702-715. 〈10.1109/TSMC.2016.2633291〉. 〈hal-01394139〉

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