Public Funding for Ai4Space Ltd

Averaged over the eight years 2004--12, about 72 objects were placed into LEO (Low Earth Orbit) per year. However, since 2012, there has been a steep increase in the number of satellites placed in LEO, with the count now running at 125 objects per year and for fast internet several companies are deploying large constellations of more than 1000 satellites in LEO. Limiting the launch rate is not feasible because it cannot be mandated. Therefore, in order to reduce the number of big objects in LEO, the only option is to actively remove large objects now in orbit. To achieve this, technology developments are required, including advanced image processing, complex guidance, navigation and control and innovative robotics to capture debris. AI4SPACE, a spinout founded by Professor Yang Gao from University of Surrey, is developing the AISat 3D visual perception and navigation system. This can use the space camera already in place within satellites and hence represents a more cost-effective, sustainable software-defined solution for debris removal as well as for space recycling, spacecraft refuelling and satellite health checks. This project will further develop our cutting edge navigation software to be used on Commercial off The Shelf (COTS) space qualified hardware for Earth orbital small satellite missions (e.g. CubeSat) and form potential partnerships with In-orbit servicing (IOS) mission operators and spacecraft platform manufacturers. Our AISat technology pushes the boundary of classical visual navigation approach by applying so called "deep learning" methods and the AISat software framework utilises a streamlined image data processing pipeline including orbital feature detection, keypoint estimation and convolutional neural networks to estimate the orientation of the space target. University of Surrey already has a research prototype validated using real-world data from the TANGO and Soyuz spacecraft. Our solution has been ranked one of the best solutions in the world within the ESA-Stanford "Grand Challenge" taking a top three position. We have identified that 86 IOS mission concepts and designs from 2025-2027 will need 3D space perception and we will use the funding from this project to integrate and validate the software ready for in-orbit demonstration opportunities in a 2023-24 timeframe.