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A SafeML extension for a unified risk assessment to diverse service robots

Takao Miyoshi, Yoshihiro Nakabo, Hidetoshi Fukui, Makoto Yashiro, I. Miyazawa, Takeshi Sakamoto, Noriaki Ando, Toru Kuga, Atsushi Kitamura, Kenichi Ohara, Tetsuya Kimura

Year
2023
Citations
2
Access
Open access

Abstract

Abstract Risk assessment is one of the important processes in the social implementation of robots. In risk assessment and safety design of systems with various stakeholders, modeling and visualization of related elements are important not only for designers but also for users. We examined the use of SafeML in the process and proposed its extension for the purpose for missing elements.

Keywords

Extension (predicate logic)Computer scienceRobotProcess (computing)Service (business)Risk analysis (engineering)Risk assessmentVisualizationKnowledge managementArtificial intelligence

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