Machine Learning and Robotics
Our group focuses on reinforcement learning, deep learning, nonlinear system identification, state estimation, and data analytics. We also employ evolutionary and hybrid algorithms to solve hard optimization problems. Applications of our methods range from robotics to dialog systems.
Research topics include
- Deep learning for visual navigation and dialog systems
- Symbolic regression for data-driven modeling
- Model-based reinforcement learning and optimal control
- Big data analytics and visualization
Turtlebot navigating in an office using a deep network for visual navigation.