SMOF - A Safety MOnitoring Framework for Autonomous Systems - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Systems, Man, and Cybernetics: Systems Année : 2018

SMOF - A Safety MOnitoring Framework for Autonomous Systems

Résumé

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.
Fichier principal
Vignette du fichier
revue9.pdf (1007.52 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01394139 , version 1 (23-01-2017)

Identifiants

Citer

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, 2018, 48 (5), pp.702-715. ⟨10.1109/TSMC.2016.2633291⟩. ⟨hal-01394139⟩
697 Consultations
1352 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More