Leicester University receives over £600K for AI algorithm shrinking method

It is one of over 20 national space projects announced by DSIT Secretary of State Peter Kyle on the opening day of the Farnborough International Airshow (FIA), on July 22, 2024. 

Worth £33m, the projects come from the UK Space Agency’s National Space Innovation Programme, which is designed to invest in high-potential technologies, drive innovation and unlock growth across the UK.

Specifically, Leicester’s REALM (Rapid information extraction for environmental remote sensing on board spacecraft through application of light Machine Learning models in payload computing systems) project has received £690,000 in funding. 

It will be a multidisciplinary project led by Leicester University, involving its School of Computing and Mathematical Sciences and School of Physics and Astronomy, as well as Space Park Leicester, the University’s £100m science and innovation park.

According to the researchers, the project aims to develop and demonstrate streamlined machine learning algorithms capable of complying with spacecraft power and computing performance requirements using drones.

Current machine learning algorithms are too large and complex to be accommodated on the limited power and performance of spacecraft computing systems, the researchers said, which presents a barrier to enabling smarter spacecraft.

REALM aims to address this issue by using a novel sparse-split-parallelism (SSP) design framework that can compress a large multi-spectral remote sensing deep learning algorithm by at least 45 per cent without any performance impact.

The researchers said that the algorithm's performance will be demonstrated on a small-scale space-compatible graphical processing unit (GPU) and its effectiveness will be validated by flying it on a drone equipped with a multispectral payload as a preliminary step towards space readiness in collaboration with commercial partners.

REALM is one of 15 ‘Kick Starter’ projects that will receive £9m between them, aiming to support technologies and applications that are in an earlier stage of development and increase their readiness for use in commercial and scientific endeavours. 

The projects cover a wide range of space-related capabilities, from in-orbit servicing and manufacturing, as well as advanced material development and the use of satellite imagery. Eight further major projects will receive £24m of the total amount.

In a statement, principal investigator Professor Tanya Vladimirova, Leicester University’s School of Computing and Mathematical Sciences, said: “To date, real-time information extraction with deep-learning level performance has not been achieved from space. 

“Our novel approach to reduce algorithm size considerably while maintaining high accuracy performance provides a disruptive enabling technology poised to unlock a wide range of real-time services from space, that previously would not have been possible due to their computational complexity.”