Stanford CoRL paper adds safety filters to humanoid RL policies with no retraining needed
drmapavone · x · 2026-11-03
A Stanford AI Lab team presents 'Constrained Whole-Body Tracking for Humanoid Robots' at CoRL 2026, tackling how to make RL-powered humanoids safe without sacrificing performance.
- Safety filters enforce kinematic and dynamic constraints — including ones never seen during training
- Minimal interference with the underlying RL policy, and no retraining required
- Led by Daniel Morton with Pranit Mohnot; being presented at CoRL Austin, Poster Session 2, Tuesday evening, #204
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