About the project
In this project, you will develop methods for autonomous underwater vehicles (AUVs) to navigate precisely without external support for indefinite periods of time using sensor information and map matching techniques.
Precise navigation is a fundamental requirement for robotic competence. However, as Global Navigation Satellite Systems (GNSS) such as GPS are unavailable in water, current navigation solutions rely on separate ship or seafloor instrumentation that is costly and limits efficiency gains.
You will investigate how Simultaneous Localisation and Mapping (SLAM) techniques can minimise navigation errors by using visual and/or terrain-based observations of the environment, matching these to elements stored in self-generated or pre-loaded maps.
Although modern SLAM solutions are satisfactory for autonomous robotic missions that cover 100km trajectories and last days, they become computationally unsolvable as survey missions grow in duration and extent. With advances in high-density energy storage and efficient propulsion systems, missions covering 1000km+ and lasting several months are becoming mechanically possible.
We need better SLAM frameworks to match the mechanical developments and identify the:
- minimal navigation setups for persistent, precise navigation
- impact of adding observation sources on precision and computational complexity
In this industry funded PhD, you will have access to data from over 100 previous AUV missions. You'll develop simulations, and perform practical experiments with state-of-the-art AUV platforms and experimental facilities at the university and Sonardyne International Ltd. There will also be opportunities to participate in field work deploying robotic systems at sea during your PhD.
You will receive regular support from the supervisory team, work in a group of underwater robotics researchers, and benefit from strong collaborative links with leading international marine robotics groups including:
- National Oceanography Centre, University of Southampton
- Australian Centre for Field Robotics, University of Sydney
- Institute of Industrial Science, University of Tokyo
- Carnegie Mellon University