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eess.SY2023
Closing the Loop on Runtime Monitors with Fallback-Safe MPC
Rohan Sinha, Edward Schmerling, Marco Pavone
When we rely on deep-learned models for robotic perception, we must recognize that these models may behave unreliably on inputs dissimilar from the training data, compromising the…
eess.SY2023
Leveraging Compositional Methods for Modeling and Verification of an Autonomous Taxi System
Alessandro Pinto, Anthony Corso, Edward Schmerling
We apply a compositional formal modeling and verification method to an autonomous aircraft taxi system. We provide insights into the modeling approach and we identify several resea…