Research in LUCAS is of significant interdisciplinary nature cross engineering, computer science, transport, agriculture and environment. Broadly speaking, current research falls into three core directions:

Development of autonomous system technologies

Development of advanced algorithms/methods for autonomous vehicles such as autopilot, situation awareness, path planning, and decision making. Particular focuses are on unmanned aerial vehicles, and intelligent ground vehicles.

Ensuring the safety of autonomous system technologies

Research in this direction includes the development contingence management to enable safe operation of autonomous vehicles or, more importantly, the development of new techniques/procedures to support verification and validation of new autonomous functions/systems to provide assurance.

Application of autonomous system technologies

This is an ever growing research direction, including the applications of artificial intelligence, data mining and autonomous system technologies in a wide range of sectors, from intelligent mobility and defence to agriculture and environment monitoring.

Activities we address include but are not limited to:

Active learning

Dual control for exploitation and exploration

Model predictive control

Situational awareness

Robust decision making

Multiple moving object tracking

Bayesian inference and its particle implementation

Bayesian brief network and decision making

Machine learning and data mining

Satellite remote sensing

Cognitive search and informative planning

Computer vision and pattern recognition

Automatic worst case search and reachability analysis

Personalisation and classification