Intelligent Mobility and Autonomous Systems (IMAS)
Research in this area 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.
- Applications 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:
- Situational awareness
- Robust decision making
- Multiple moving object tracking
- Bayesian inference and its particle implementation
- Bayesian brief network and
- 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
Typical Case Studies and Applications
- Autonomous forced landing systems for unmanned aircraft
- Autonomous taxiing for ground operation of aircraft
- Remote sensing for intelligent irrigation
- Pests and disease detection and monitoring for precision farming
- Source determination and coverage estimation of chemical, biological and radiation dispersion using autonomous/mobile platforms