Fujitsu UK has combined quantum-inspired computing and Artificial Intelligence to support the transformation of space debris removal.
Fujitsu’s prototype, created in collaboration with Amazon Web Services, Astroscale UK, and the University of Glasgow, will improve mission planning so that a single spacecraft can efficiently select which pieces of space debris to remove in one mission, and at a much faster rate than is currently possible.
By deciding which debris is collected and when, Fujitsu’s quantum-inspired offering, powered by Digital Annealer, optimises the mission plan to determine the minimum-fuel and minimum-time required to bring inoperable spacecrafts or satellites safely back to the disposal orbit. Finding the optimal route to collect the space debris will save significant time and cost during the mission planning phase, and also as a consequence will improve commercial viability.
Ellen Devereux, Digital Annealer Consultant at Fujitsu UK & Ireland, commented: “All Space Debris poses a potential collision risk to the operational systems many of us take for granted – from weather forecasting to telecommunications. With the UK Space Agency’s backing, along with Astroscale UK, AWS and the University of Glasgow, we’ve designed a solution to optimise the mission planning of a servicing craft before it is sent into space – meaning organisations like Astroscale UK can pick up more debris, more quickly than ever before.
“It not only makes the process much more cost effective for those organisations needing to transfer and dispose of debris, but utilises AI and quantum inspired computing too. What we’ve learned over the course of the last six months, is that this technology has huge implications for optimisation in space; not only when it comes to cleaning up debris, but also in-orbit servicing and more. Now we better understand its potential, we can’t wait to see the technology applied during a future mission.”
Amazon Web Services provided the Cloud and AI and ML tools and services to support the project. The Amazon Sagemaker toolset was used to rapidly develop the ANNs that accurately predict the costs of orbital transfers in a fraction of the time it would take to calculate them in full. Astroscale UK, the world’s first commercial company to start a demonstration mission to remove debris from the lower Earth orbit, is providing the end-use case as a representative user of multi-target mission optimisation.