Safe Continual Domain Adaptation of Robotic Policies

How to adapt robot control policies continuously and safely after deployment on the real system

We leverage safe RL and continual learning under domain-randomized simulation to enable safe deployment-time policy adaptation in real-world robot control. More info at the project website.