CSF: Contextual Safety Filtering for Motion Generators
Presents novel safety methodology for motion generation systems with real-world robotics validation.
AI Summary
Researchers introduce CSF, a -free safety filter that reduces danger events by up to 90% for text-conditioned motion generators while preserving benign motions.
Excerpt
Text-conditioned motion generators produce trackable whole-body motion, but they have no notion of scene-dependent safety: the same action may target an object or a person. Existing safeguards either inspect the prompt, require labeled motion data, or enforce geometric constraints; therefore, they do not directly account for how scene context changes a motion's meaning. We introduce contextual safety filtering (CSF), a training-free filter that grounds natural-language safety rules in safe and u