Funding
Self-funded
Project code
SMDE4610220
Department
School of Electrical and Mechanical EngineeringStart dates
October, February and April
Application deadline
Applications accepted all year round
Applications are invited for a self-funded 3-year PhD.
The PhD will be based in the Faculty of Technology, and will be supervised by Dr Ya Huang, Dr Andrea Bucchi and Professor Hui Yu.
The work on this project will:
- Implement existing stereo-vision pipelines of epipolar search approach, and variational surface shape model based dense 3D reconstruction of moving wave
- Develop physics wave model to simulate in detail wave-induced load on the vessel
- Modify the variational approach to a sparse surface wave model by incorporating a statistical model of hydrodynamics in the optimisation functionals for matching to allow real time estimation of wave propagation parameters
The project intents to develop a stereo-vision based feature extraction pipeline of oncoming waves at close-proximity. The machine vision system will be deployed on fast marine crafts as a key part of a shock mitigation controller for autonomous surface vehicle that considers the well-being of its human occupants.
The outcome will devise understanding and correlation between close-range wave characteristics with human biomechanic responses to mechanical shock and vibration at sea. The results will be equally relevant to autonomous off-road vehicles with human occupants.
The School of Electrical and Mechanical Engineering owns two unmanned surface test vehicles and a FLIR® stereo vision camera system dedicated to this project for wave data collection and machine vision algorithm validation. The project will start with comparing and adapting existing stereo vision techniques to achieve off-line wave characterisation. The new in-the-loop feature detector and the unique close-wave imagery data made available will make a significant contribution to the wider machine vision community for outdoor mobile systems and the marine industry.
The visual features will form an important part of the shock-mitigating navigational decisions that are key to the future surface vehicles for safer transport of personnel and casualties. The project is aligned with the University’s vision to build global and national partnership through the boundary-breaking themes of future transportation and intelligent systems.
The successful candidate is expected to collaborate with project partners from areas of visual computing, hydrodynamic modelling, biomechanics and industrial partners in the maritime industry. Attendance at conferences, project meetings, and workshops is also anticipated.
Fees and funding
Visit the research subject area page for fees and funding information for this project.
Funding availability: Self-funded PhD students only.
PhD full-time and part-time courses are eligible for the (UK and EU students only).
Entry requirements
You'll need an upper second class honours degree from an internationally recognised university or a Master’s degree in Robotics, Computer Science, Electronics, Mechanics, Mathematics, Physics or a similar discipline. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.
How to apply
We’d encourage you to contact Dr Ya Huang at ya.huang@port.ac.uk to discuss your interest before you apply, quoting the project code.
Apply
When you are ready to apply, please follow the 'Apply now' link on the Mechanical and Design Engineering PhD subject area page and select the link for the relevant intake.
If you want to be considered for this self-funded PhD opportunity you must quote project code SMDE4610220 when applying.