Innovation in Planning Space Debris Removal Missions Using Artificial Intelligence and Quantum-Inspired Computing

Snelling, D., Devereux, E., Payne, N., Nuckley, M., Viavattene, G. , Ceriotti, M. , Wokes, S., Di Mauro, G. and Brettle, H. (2021) Innovation in Planning Space Debris Removal Missions Using Artificial Intelligence and Quantum-Inspired Computing. 8th European Conference on Space Debris, Darmstadt, Germany, 20-23 Apr 2021.

Abstract

This paper proposes an optimisation solution and tool-set for planning an active debris removal mission, enabling a single spacecraft to deorbit multiple space debris objects in one mission efficiently. A two-step strategy is proposed; first, an Artificial Neural Network is trained to predict the cost of orbital transfer to and disposal of a range of debris objects quickly. Then, this information is used to plan a mission of four captures from 100 possible debris targets using Fujitsu’s quantum-inspired optimisation technology, called Digital Annealer, by formulating the problem as a quadratic unconstrained binary optimisation. In validation, this platform produced a 25% faster mission, using 18% less propellant when compared to an expert’s attempt to plan the mission using the same assumptions, this solution was found 170,000 times faster than current methods.

• Item Type: Conference or Workshop Item
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ceriotti, Dr Matteo and Viavattene, Giulia
• Authors: Snelling, D., Devereux, E., Payne, N., Nuckley, M., Viavattene, G., Ceriotti, M., Wokes, S., Di Mauro, G., and Brettle, H.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy

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