MACHINE LEARNING FOR BIO-INSPIRED NAVIGATION

This project will be concerned with assessing and replicating the different methods that animals use to navigate over long distances during migration. The initial emphasis will be on the sensory ability of birds, but the project will review all current theories for animal navigation and migration. Animals have a range of sensory inputs that we as humans lack. Examples include magnetic sensors, landmark recognition, and the ability to detect polarised light. Improvements to magnetic sensing from the UK quantum technology programme are increasing interest in the use of magnetic sensors for navigation, but there are still issues around the effect of stray magnetic fields caused by electronics and other metal components. Image based navigation has also been studied previously, but with the ability to distinguish polarised light, there is scope to combine ground feature databases with information from polarised solar illumination. The objective of the PhD will be to identify bio-inspired sensors that could be used in Positioning Navigation and Timing (PNT) applications and to develop a processing architecture that would allow such sensors to form part of a fused PNT solution.