Modelling and Control

Modelling and control form an important part of the fundamentals of robotics. Our research will advance new learning in modelling and control for robotics through combining classical modelling techniques and optimisation-based control algorithms with state-of-the-art deep learning algorithms.

Our areas of focus include a wide spectrum of applications in robotics. Our research on modelling and analysis of human motion will provide enhanced human-robot interaction and early diagnosis of neurodegenerative diseases. We use AI-based control algorithms in autonomous drones and driverless vehicles to guarantee safe operations of autonomous systems in complex environments. We have a special interest in shared autonomy, in which we ask questions about how automatic control systems should be designed when human operators work with autonomous robots.