SAFE-CHEM: Uncertainty-Aware Policy Switching for Robust Robotic Chemistry
This work proposes SAFE-CHEM, an uncertainty-aware framework designed for robust, learning-based robotic chemists that introduces a hybrid control architecture that autonomously switches from the learned policy to a deterministic, rule-based backup controller when uncertainty exceeds a calibrated safety threshold.