A UML-based method for risk analysis of human-robot interactions

Abstract

Safety is a major concern for robots that interact physically with humans. We propose a risk analysis method based on deviation analysis of system usage scenarios that allows the identification of major risks. Scenarios are described with the common Unified Modeling Language (UML), and risk analysis is performed with the guideword-based collaborative method HAZOP (HAZard OP-erability). We adapt HAZOP attributes and guidewords for generic interpretation of UML use-case and sequence diagrams describing human-robot interactions. This approach has been systematically applied for the analysis of two quite different robots working in a human environment: a mobile manipulator and a robotic strolling assistant. When applied, the method gave conclusive evidence that the modeled systems were not safe. A CASE tool to support this method is also presented.