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Development of Robust Simultaneous Localisation and Mapping Techniques for Autonomous Underwater Vehicles Operating under the Polar Sea-Ice


Project Description

Project Rationale:
Despite the considerable effort directed towards AUV navigation, a self-contained solution remains a key challenge. Due to the cumulative error that inertial navigation experiences with time, AUVs typically require an external navigation support or regular surfacing to obtain GPS fixes and limit the error [1], which options can be undesirable/unavailable in certain applications (e.g. deep-water and/or under-ice deployments). In response to the presently limited navigation capability, this project will focus on the development of robust navigation techniques for high-powered AUVs that relying on on-board sensors and efficient algorithms will enable navigation in GPS-denied environments. SLAM is a powerful technique where a robot builds the map of the surrounding environment and concurrently localises itself within that map. Although SLAM has been proven to be effective for mobile robots operating in structured environments, the application of these techniques in the highly unstructured underwater domain is immature with outstanding challenges to be addressed. The candidate will be required to develop robust and computationally feasible in real-time sonar-based SLAM algorithms. Upon the successful demonstration of the effectiveness of the algorithms in computer simulations (with respect to the environmental suitability), the candidate will have the opportunity to test the algorithm in real-time via field experiments.

Funding Notes

You can apply for fully-funded studentships (stipend and fees) from INSPIRE if you:
Are a UK or EU national.
Have no restrictions on how long you can stay in the UK.
Have been 'ordinarily resident' in the UK for 3 years prior to the start of the project.

Please click View Website for more information on eligibilty and how to apply

References

[1] Paull, Liam, et al. "AUV navigation and localization: A review." IEEE Journal of Oceanic Engineering 39.1 (2013): 131-149.
[2] Palomer, Albert, Pere Ridao, and David Ribas. "Multibeam 3D underwater SLAM with probabilistic registration." Sensors 16.4 (2016): 560.
[3] Ribas, David, et al. "Underwater SLAM in a marina environment." 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2007.

How good is research at University of Southampton in Earth Systems and Environmental Sciences?

FTE Category A staff submitted: 68.62

Research output data provided by the Research Excellence Framework (REF)

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