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Predictive Runtime Verification of Skill-Based Robotic Systems Using Petri Nets

Baptiste Pelletier, Charles Lesire, Christophe Grand, David Doose, Mathieu ROGNANT

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Abstract

This work presents a novel approach for the online supervision of robotic systems assembled from multiple complex components with skillset-based architectures, using Petri nets (PN). Predictive runtime verification is performed, which warns the system user about actions that would lead to the violation of safety specifications, using online model-checking tools on the system PNs.

Index terms

Formal Methods in Robotics and Automation