Improving Subsea Navigation Using Environment Observations For Long Term Autonomy

Supervisory Team:   Blair Thornton (Engineering)

Christine Evers (Electronics and Computer Science)

Adam Prügel-Bennett (Electronics and Computer Science)

Christine Currie (Mathematical Sciences)

Darryl Newborough (Sonardyne International Ltd.)

Project description

This PhD will develop methods to use sensor information and map-matching techniques to allow autonomous underwater vehicles (AUVs) to navigate precisely for indefinite periods of time without relying on any external support infrastructure.

Precise navigation is a fundamental requirement for robotic competence. However, Global Navigation Satellite Systems (GNSS) such as GPS are unavailable in water, and current navigation solutions rely on separate ship or seafloor instrumentation that dominates operational costs and limit efficiency gain.

You will investigate how Simultaneous Localisation and Mapping (SLAM) techniques can minimise navigation errors by taking advantage of 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:

·        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 past AUV missions. You will develop both simulations and perform practical experiments with state-of-the-art AUV platforms and experimental facilities at UoS and Sonardyne International Ltd, and there will be opportunities to participate in field work deploying robotic systems at sea during your PhD.

You will receive regular support from the supervisory team and work within a group of underwater robotics researchers and benefit from strong collaborative links with leading international marine robotics groups (includes NOC, Southampton; ACFR, USydney; IIS, UTokyo and Carnegie Melon University).

Entry Requirements

A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).

Closing date: 16^th September 2022.

Funding: For UK students, Tuition Fees and a stipend of £15,609 tax-free per annum for up to 3.5 years and an addition research and training support grant of £2000 per annum for research related expenditures.

How To Apply

Applications should be made online. Select programme type (Research), 2022/23, Faculty of Physical Sciences and Engineering, next page select “PhD Engineering & Environment (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Blair Thornton

Applications should include:

Curriculum Vitae

Two reference letters

Degree Transcripts to date

Apply online: https://www.southampton.ac.uk/courses/how-to-apply/postgraduate-applications.page

For further information please contact: [Email Address Removed]

The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.