Control-Aware Active Perception for Underwater Inspection
Not stated
- Funding
- Funded PhD Project (UK Students Only)
- Application deadline
- Year-round applications
About the project
About the Project 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 Second Supervisor: James Taylor Lancaster University Industry Partner: Sonomatic (Confirmed) Project Start: October 2026 Target Background: Control, mechatronics, robotics Industrial Funding: None at this stage (Sought) Advert Close Date: August 2026 Programme: 4 year Engineering Doctorate (EngD) with industry placement 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. 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. How to apply Email the team