Synthesis of Safety Rules for Active Monitoring: Application to an Airport Light Measurement Robot

Masson, Lola; Guiochet, Jérémie; Waeselynck, Hélène; Desfosses, Augustin; Laval, Marc

doi:10.1109/irc.2017.11

Cited by 6 publications

(3 citation statements)

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“…A safety invariant is a logic formula over a set of observable variables, derived from sensor values. The formalization of hazards as invariants may reveal the need for additional observation means, like in [17] where the original system design was revised to add sensors.…”

Section: Safety Invariants Margins and Statesmentioning

confidence: 99%

“…The SMOF method and tool have been applied to real examples of robots: an industrial co-worker in a manufacturing setting [15], and a maintenance robot in airfield [17]. Examples and tutorials can be found online [2].…”

Section: Smof Toolingmentioning

confidence: 99%

“…However, this would not work for all systems, as demonstrated by the maintenance robot studied in [17]. For this robot, some warning states do correspond to a nominal behavior and are essential to the accomplishment of the maintenance mission.…”

Section: On Tuning Permissiveness Propertiesmentioning

confidence: 99%

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Tuning Permissiveness of Active Safety Monitors for Autonomous Systems

Masson

Guiochet

Waeselynck

et al. 2018

Lecture Notes in Computer Science

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Abstract. Robots and autonomous systems have become a part of our everyday life, therefore guaranteeing their safety is crucial. Among the possible ways to do so, monitoring is widely used, but few methods exist to systematically generate safety rules to implement such monitors. Particularly, building safety monitors that do not constrain excessively the system's ability to perform its tasks is necessary as those systems operate with few human interventions. We propose in this paper a method to take into account the system's desired tasks in the specification of strategies for monitors and apply it to a case study. We show that we allow more strategies to be found and we facilitate the reasoning about the trade-off between safety and availability.

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Section: Safety Invariants Margins and Statesmentioning

confidence: 99%

Section: Smof Toolingmentioning

confidence: 99%