Demo Abstract: Real-Time Out-of-Distribution Detection on a Mobile Robot

Understand

In a cyber-physical system such as an autonomous vehicle (AV), machine learning (ML) models can be used to navigate and identify objects that may interfere with the vehicle's operation.

• However, ML models are unlikely to make accurate decisions when presented with data outside their training distribution.
• Out-of-distribution (OOD) detection can act as a safety monitor for ML models by identifying such samples at run time.
• However, in safety critical systems like AVs, OOD detection needs to satisfy real-time constraints in addition to functional requirements.