Uncertainty Synthesis for Trusted Autonomy
Control algorithms with provable guarantees for systems that learn - from Mars powered descent to autonomous vehicles
Our research spans five core areas, combining theoretical insights with practical applications to advance the state of autonomous systems. Each area represents a fundamental pillar of our work in robotics, control, and artificial intelligence.
Control algorithms with provable guarantees for systems that learn - from Mars powered descent to autonomous vehicles
How machines decide under incomplete information - bounded rationality, learning, and control that adapts in real time
Getting there safely and fast - planning and control for agile vehicles, from racing cars to spacecraft in proximity operations
Pursuit, evasion, and cooperation - game-theoretic strategies for teams of agents that must decide without a central authority
Autonomy far from home - navigation, rendezvous, and manipulation for spacecraft that cannot wait for instructions from Earth