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SafeLoop: Risk-Aware Rollback for Vision-Language-Action Manipulation

arXiv · AI, language, vision and robotics · article · Sep 22, 2026 · UTC

Recent vision-language-action (VLA) models are promising for general-purpose manipulation, but long-horizon execution remains fragile. Small state-estimation or control errors can lead to irreversible failures (e.g., collisions and object drops). Avoiding these risks requires a proactive safety mechanism capable of anticipating hazards. In this paper, we introduce SafeLoop, a non-invasive external wrapper that adds hazard prediction and rollback-based recovery to a VLA model without changing its parameters. SafeLoop trains a risk predictor from vision and proprioception to output four values:

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Evidence & attribution

First collected: 2026-09-23T04:11:12.117Z. This is not the publication date.