Less than a year after the UK Space Agency committed £1 million in funding to combat the growing problem of space junk, Fujitsu UK has announced the successful combination of quantum-inspired computing and Artificial Intelligence to transform space debris removal.
Space debris
An artist's impression of the space debris in Earth's orbit. Photo: ESA–P. Carril
Fujitsu’s prototype, which was 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. The removal of space debris is key to sustainability in space, reducing, or even preventing, the risk of obsolete spacecraft colliding with new and existing satellites.
Fujistu also claims that its technology will help to reduce the risk of catastrophic collisions in orbit which could create thousands of other pieces of new debris, all of which pose a very real threat to working satellites in orbit.
Read more: ESA to send huge claw into space to remove space junk
By carefully deciding which debris is collected and when, the quantum-inspired technology, powered by Digital Annealer, optimises the mission plan to determine the minimum fuel and minimum time required to bring inoperable spacecraft 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.
With 2,350 non-working satellites currently in orbit, and more than 28,000 pieces of debris being tracked by Space Surveillance networks, Fujitsu says its technology will help the UK to grow its market share in the space sector, and further support the UK Government’s commitment to a more sustainable future overall.
The research has been carried out as part of the UK Space Agency grant “Advancing Research into Space Surveillance and Tracking”. The project, which was developed over six months in accordance with Government Digital Services guidelines, leverages both Artificial Neural Network (ANN)-based rapid trajectory design algorithms, developed by the University of Glasgow, alongside Fujitsu’s Digital Annealer and Quantum Inspired Optimisation Services to solve some of the main optimisation problems associated with ADR (Active Debris Removal) mission planning design.
Ellen Devereux, Digital Annealer Consultant at Fujitsu UK & Ireland, said: "All space debris poses a potential collision risk to the operational systems many of us take for granted – from weather forecasting to telecommunications... 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."
Read more: Wooden satellites being developed in Japan to curb space junk
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 is the world’s first commercial company to start a demonstration mission to remove debris from the lower Earth orbit. The company is providing the end-use case as a representative user of multi-target mission optimisation.
Fujitsu, who spearheaded the project, is one of just seven UK companies to be awarded a share of over £1 million from the UK Space Agency to help track debris in space.
Jacob Geer, Head of Space Surveillance and Tracking, UK Space Agency, said: "Monitoring hazardous space objects is vital for the protection of services we all rely on - from communications devices to satellite navigation.
"This project is one of the first examples of quantum-inspired computing working with artificial intelligence to solve the problems space debris causes, but it's unlikely to be the last."
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