AI RESEARCH
RoboFAC: A Comprehensive Framework for Robotic Failure Analysis and Correction
arXiv CS.AI
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ArXi:2505.12224v4 Announce Type: replace-cross Vision-Language-Action (VLA) models have recently advanced robotic manipulation by translating natural-language instructions and visual observations into control actions. However, existing VLAs are primarily trained on successful expert nstrations and lack structured supervision for failure diagnosis and recovery, limiting robustness in open-world scenarios. To address this limitation, we propose the Robotic Failure Analysis and Correction (RoboFAC) framework.