Model-Driven Safety Assessment of Robotic Systems

Nataliya Yakymets (1, 2) , Saadia Dhouib (1, 2) , Hadi Jaber (1, 2) , Agnes Lanusse (1, 2)

1 LIST (CEA) - Laboratoire d'Intégration des Systèmes et des Technologies
2 DILS (CEA, LIST) - Département Ingénierie Logiciels et Systèmes

Robotic systems (RSs) are often used for performing critical tasks with little or no human intervention. Such RSs must satisfy certain dependability requirements including reliability, availability, security and safety. In this paper, we focus on the safety aspect and propose a methodology and associated framework for safety assessment of RSs in the early phases of development. The methodology relies upon model-driven engineering approach and describes a preliminary safety assessment of safety-critical RSs using fault tree (FT) analysis (FTA). The framework supports a domain specific language for RSs called RobotML and includes facilities (i) to automatically generate or manually construct FTs and perform both qualitative and quantitative FTA, (ii) to make semantic connections with formal verification and FTA tools, (iii) to represent FTA results in the RobotML modeling environment. In the case study, we illustrate the proposed methodology and framework by considering a mobile robot developed in the scope of the Proteus project.

Domaines: Informatique [cs]

Nataliya Yakymets, Saadia Dhouib, Hadi Jaber, Agnes Lanusse. Model-Driven Safety Assessment of Robotic Systems. 2013 (IEEE/RSJ) International Conference on Intelligent Robots and Systems, Nov 2013, Tokyo, Japan. ⟨cea-01810068⟩