Learning Control Theory and Foundations
Learning algorithms hold great promise for improving a robot's performance whenever a-priori models are not sufficiently accurate. We have developed...
Self-Driving Cars
As part of the SAE Autodrive Challenge, students in our lab will be working on designing, developing, and testing a self-driving car over the next...
High-Performance Robot Control and Planning
This project explores advanced control and planning algorithms, and their applicability to robotics problems. To achieve reliable robot operations...
Safe and Robust Robot Learning in Unknown Environments
Learning can be used to improve the performance of a robotic system in a complex environment. However, providing safety guarantees during the...
Vision-Based Flying and Driving
We use vision to achieve robot localization and navigation without using external infrastructure. Our ground robot experiments localize based on 3D...
Aerial and Ground Robot Racing
This project explores the physical limits of ground and aerial robots. When operating robots in these regimes, unknown dynamic effects (for example,...