Research Overview
Our lab works on developing theory and technologies for robot control. We extend traditional robot control design methods by incorporating machine learning using systematic approaches. We emphasize learning-based control strategies that are provably correct. Our members acquire expertise in topics from control systems, robotics, optimization, and machine learning. We currently focus on the following areas:
- Contact-rich manipulation
- Verification of learned neural network controllers
- Navigation without localization
