You can enforce formal safety constraints on pretrained robotics models without retraining by adjusting their output distributions at inference time using temporal logic specifications.
This paper adds safety guardrails to robotics foundation models by reshaping their action distributions at runtime to satisfy formal specifications. Instead of retraining the model, it uses forward simulation to ensure the robot meets time-dependent constraints like "visit location A before time T, then location B" while staying as close as possible to the model's original decisions.