Unpacking Failure Modes of Generative Policies: Runtime Monitoring of Consistency and Progress Christopher Agia , Rohan Sinha , Jingyun Yang ,Zi-ang Cao, Rika Antonova , Marco Pavone , Jeannette Bohg Conference on Robot Learning (CoRL), 2024[arXiv][Project Site] Robot behavior policies trained via imitation learning are prone to failure under conditions that deviate from their training data. In this work, we present Sentinel, a runtime monitor that detects unknown failures (requiring no data of failures) of generative robot policies at deployment time.