The Algorithms, Optimization, and Control Lab (AOCL) at UBC conducts research at the intersection of control, optimization, and computing. We apply control, optimization, game-theory and machine learning to solve problems in energy, manufacturing, robotics, and aerospace.
Current research in the lab involves:
- Model Predictive Control
- Multi-agent Control and Algorithmic Game Theory
- Real-time, Embedded, and Distributed Optimization
- Iterative Learning Control
with applications in energy, manufacturing, and robotics including:
- Large-scale Infrastructure (e.g., energy, buildings, transport, logistics)
- Autonomous Vehicles and Multi-agent Robotics
- Additive Manufacturing (3D printers)