Abstract
A crucial aspect of physical human–robot collaboration (HRC) is to maintain a safe common workspace for human operator. However, close proximity between human–robot and unpredictability of human behavior raises serious challenges in terms of safety. This article proposes a risk analysis methodology for collaborative robotic applications, which is compatible with well-known standards in the area and relies on formal verification techniques to automate the traditional risk analysis methods. In particular, the methodology relies on temporal logic-based models to describe the different possible ways in which tasks can be carried out, and on fully automated formal verification techniques to explore the corresponding state space to detect and modify the hazardous situations at early stages of system design.
Highlights
H UMAN–ROBOT collaboration (HRC) in industrial settings enhances the flexibility and adaptability of robotic systems for production
We formally model the system through a temporal logic language
The first requirement is accomplished using a temporal logic language, called TRIO [52], which is capable of expressing the evolution over time of phenomena of interest (e.g., “the operator enters a robotic cell before a robot moves”) and is general enough to describe decidable and undecidable models, over discrete and continuous time
Summary
H UMAN–ROBOT collaboration (HRC) in industrial settings enhances the flexibility and adaptability of robotic systems for production. The environment can change, due to mobile resources, tool changing, modification of the layout, and process locations, so that the specifications of the system need to be re-evaluated The safety of such evolving systems should not be verified as a static property, but rather according to the behavior of the system in actual situations. This article introduces a rigorous, iterative methodology— based on formal methods—to guarantee the safety of physical HRC systems.
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