My research focuses on developing autonomous robotic systems capable of operating reliably in uncertain and challenging environments. The program is organized around four interconnected research themes, with these capabilities brought together in real-world applications.
Developing intelligent decision-making algorithms that enable autonomous robots to plan, coordinate, and adapt in uncertain and dynamic environments using reinforcement learning, probabilistic planning, and multi-agent autonomy.
Advancing robotic perception through simultaneous localisation and mapping (SLAM), sensor fusion, and vision-based localisation to enable reliable operation in complex and GPS-denied environments.
Developing Bayesian estimation and Random Finite Set (RFS) based algorithms for robust multi-object tracking, state estimation, and situational awareness under uncertainty.
Designing and deploying autonomous aerial, ground, and marine robotic systems that integrate perception, estimation, and decision-making for real-world field applications.
Developing autonomous and multi-robot systems for exploration, mapping, navigation, and operation in unknown, unstructured, and challenging environments.
Applying autonomous robotic systems, sensing, mapping, and perception to marine science, environmental monitoring, and field data collection.
Applying robotics, automation, perception, and intelligent decision-making to industrial systems, infrastructure inspection, asset monitoring, and process environments.
Developing autonomous and multi-robot capabilities for decision-making, coordination, tracking, and operation in adversarial and security-relevant environments.