EPSRC - Neuromorphic Underwater Star Tracking for Navigation and Monitoring

About the Project

When equipped with an upward-facing camera, underwater vehicles can detect objects above the water surface, from insects to satellites. However, the water-air interface introduces rapid optical distortions caused by surface waves, making accurate position estimation exceptionally difficult. Conventional high-frame-rate cameras can capture these dynamics but require high-power processing units to handle the data in real-time. Neuromorphic event cameras are a promising alternative to tackle this problem. Their smart pixels can detect scene changes with sub-millisecond temporal accuracy, and unlike conventional cameras, they do not generate frames but a sparse stream of events that can be processed in real-time with little power. However, such processing requires the development of novel algorithms, fundamentally different from those used in conventional computer vision.

The primary aim of this project is to research and develop novel systems and algorithms for "looking up" through the water surface. The research will focus on detecting and tracking objects with neuromorphic event cameras and using catalogued objects, such as stars, to compensate the effect of waves. Key research directions include the combination of advanced caustics renderers with event-based simulators to develop distortion-compensation algorithms, followed by rigorous experimental validation using waterproofed hardware in wave pools and open-sea environments. The project will also explore the implementation of these algorithms on embedded platforms (CPUs, FPGAs, and neuromorphic accelerators) and the potential for sensor fusion with sonar data.

We are seeking a highly motivated and creative candidate with a strong academic background in Computer Science, Engineering (Electrical, Mechatronics, or Robotics), Physics, or a related discipline. The successful applicant will have a solid foundation in programming (Python, Rust, C, C++…) and an interest in software simulation. Experience with embedded systems or FPGAs is highly desirable but not essential. The ideal applicant will possess excellent analytical skills and a proactive mindset, as the project involves a mix of high-level algorithmic development and hands-on experimental validation in challenging aquatic environments.

The student will join the International Centre for Neuromorphic Systems (ICNS), a world-leading hub for brain-inspired technology, in an integral partnership with Thales, a global leader in underwater and defence systems. This collaboration provides the student with unparalleled domain expertise and access to specialised experimental facilities, including advanced wave pools for controlled data collection. The supervisory team offers expertise across neuromorphic engineering, embedded systems, and maritime applications.