PhD Studentship: 3D Mapping of Geometrically Complex Seafloor Infrastructures Using Marine Vehicles

University of Southampton - Fluid Structure Interactions, Faculty of Engineering and the Environment

The aim of this Ph.D. is to develop instruments and methods to generate high-resolution, georeferenced maps of geometrically complex deep-seafloor energy infrastructures, such as those used in the oil and gas industry, using an Autonomous Underwater Vehicle (AUV).

Decommissioning is the final chapter in the lifecycle of all sub-sea infrastructure, which often spans >20 years from fabrication and installation. The projected expenditure for decommissioning of ageing and retired seafloor installations in the UK continental shelf is estimated at >£30bn with >8,000 installations in the North-sea alone. As a result, methods to efficiently map seafloor installations are in need for effective planning and informed decision making regarding decommissioning activities.

The aim of this project is to

  • develop a full field immersive 3D camera system that can be used to navigate through and map environments with large vertical structures and overhangs, and
  • develop a simultaneous localization and mapping (SLAM) algorithm to determine the AUV’s position and generate dimensionally accurate 3D reconstructions of the environment.

The first part of the project will modify an existing visual mapping instrument to map the seafloor so that it can perceive vertical and overhanging structures around the AUV. The second part of the project will develop a SLAM algorithm that can handle the measurements made by the sensor and leverage some prior, imperfect knowledge about the individual units present on the seafloor and their arrangement, i.e. a rough map. An important aspect of this is to not over constrain the solution, since prior information is likely to contain inaccuracies due to imperfectly documented deviations from initial plans during infrastructure installation and changes during maintenance as well as undocumented changes due to corrosion, damage and sedimentation.

We are looking for a student with a 1st Class Masters-level or equivalent qualification in engineering, who is willing to participate in research expeditions at sea and travel abroad for several weeks to work with overseas institutes. The student should be familiar with electronics and programming (python and C++) and will be trained in computer vision and probabilistic methods for localisation and mapping.

Shortlisting of candidates will take place in June 2018. Interviews will be held in June 2018.

If you wish to discuss any details of the project informally, please contact Dr Blair Thornton, Email:, Tel: +44 (0) 23 8059 7322

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