Home / PhD Opportunities / Control-Aware Active Perception for Underwater Inspection
Open now | Lancaster University | In-service availability | Sonomatic
Control-Aware Active Perception for Underwater Inspection
Develop autonomous underwater inspection systems that combine control of the vehicle with structural assessment to obtain reliable, uncertainty-aware integrity maps.
Lead Supervisor
David Cheneler
Lancaster University
Industry Partner
Sonomatic
Confirmed
Project Start
October 2026
Target Background
Control, mechatronics, robotics
Second Supervisor
James Taylor
Lancaster University
Industrial Funding
None at this stage
Sought
Advert Close Date
August 2026
Programme
4 year Engineering Doctorate (EngD)
with industry placement
Project summary
Aims and objectives
Aim: develop a control-aware active perception framework for autonomous underwater structural integrity inspection, enabling a robotic system to adapt its motion, contact conditions and sensing actions to acquire high-quality multi-modal inspection data and produce reliable, uncertainty-aware assessments of defects.
Objectives:
Establish a control and integrity-assessment framework.
Develop control-aware sensing and acquisition-quality models.
Develop active inspection planning and closed-loop control.
Develop multi-modal defect interpretation and uncertainty-aware integrity mapping.
Alignment to STAND-UP impact targets
>50% reduction in overall build or decommissioning process time
>40% reduction in maintenance time
>30% reduction in person hours on builds (not applicable)
Apply for this project
Contact the lead supervisor or programme team to discuss your interest. Full application instructions are on the How to Apply page.
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How you scan matters as much as what you scan.
This EngD project will develop autonomous underwater inspection systems for assessing the structural integrity of submerged assets such as submarines, ship hulls, offshore structures and marine infrastructure using non-destructive testing (NDT).
While underwater unmanned vehicles (UUVs) can increasingly map and survey assets, reliable detection of cracks, corrosion and other hidden defects still depends on high-quality sensing under difficult, highly variable conditions. The vehicle's control history partly determines the information content of the NDT signal, so structural inference must be conditioned on sensing actions, contact state and motion uncertainty.
By combining the control of the system with the structural assessment, the project creates control-aware active perception methods that allow an autonomous platform to decide not only what to inspect, but also how to position itself to obtain the most informative measurements. This results in safer maritime operations, reduced inspection cost and improved resilience of critical underwater infrastructure.
Ready to apply?
Read the entry requirements, application process and FAQs on the How to Apply page.