Multi-agent robotic systems for optimal characterisation and mapping of complex environments, using coordinated mobile sensor networks deployed on ground-based wheeled robots and unmanned aerial vehicles (UAVs). 

Control methods for the robust coordination of heterogeneous robotic systems, enabling reliable cooperation between multiple autonomous platforms in dynamic and uncertain environments.

Control and motion planning methods for dexterous robotic manipulation, enabling precise, adaptive interaction with complex objects and unstructured environments.

Autonomy, control, and sensing for submersible autonomous vehicles, supporting robust navigation, mapping, and monitoring in challenging underwater environments.

Machine learning and digital signal processing methods for robust audio and speech systems, with a focus on active noise control and multilingual speech translation in real-world environments.