Autonomous Decision and Control Lab
The lab develops AI methods to control complex, uncertain autonomous systems. It works on autonomous aerospace platforms, from space probes to drones and telescopes for tracking space debris, and has also studied ecological systems and autonomous cars. Core technology includes partially observable Markov decision processes (POMDPs) and online tree search algorithms for decision making under uncertainty. The work spans theory, numerical simulation, and hardware experiments, and often involves collaboration with researchers and operators in related fields. The focus is on scalable, real-world deployment across diverse environments and applications.
Autonomous Decision and Control Lab
The lab develops AI methods to control complex, uncertain autonomous systems. It works on autonomous aerospace platforms, from space probes to drones and telescopes for tracking space debris, and has also studied ecological systems and autonomous cars. Core technology includes partially observable Markov decision processes (POMDPs) and online tree search algorithms for decision making under uncertainty. The work spans theory, numerical simulation, and hardware experiments, and often involves collaboration with researchers and operators in related fields. The focus is on scalable, real-world deployment across diverse environments and applications.