robotics
Angela Schoellig
safe reinforcement learning
learning-based control
control theory
robot learning
Schoellig’s group connects control-theoretic guarantees with reinforcement learning and robot learning, especially for safe learning-based autonomy.
Pros
- Recognised leader in safe learning-based control with strong ICRA/IROS/L4DC output
- Well-resourced via TUM, Munich robotics ecosystem, ELLIS and ERC-level funding
- Clear control-plus-RL fit with rigorous safety and real-robot validation
Learning Systems and Robotics Lab
A quick heads-up: This list is a work in progress! The focus tags and pros are AI-generated, so they might occasionally miss the mark. If you spot any missing labs, notice an error, or have ideas for improvements, please feel free to open a pull request. We’d love your help making this better!