Developing autonomous robotic systems capable of operating reliably in uncertain and challenging environments.
My research integrates intelligent decision-making, probabilistic state estimation, robotic perception, and autonomous robotic systems to address challenges in marine robotics, environmental monitoring, industrial automation, and defence.
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.
Applying autonomous robotics and artificial intelligence to solve real-world challenges in environmental monitoring, marine science, industrial automation, infrastructure inspection, and defence.