5 papers
Comparing Behavioural Cloning and Reinforcement Learning for Spacecraft Guidance and Control Networks
Harry Holt, Sebastien Origer, Dario Izzo
Guidance & control networks (G&CNETs) provide a promising alternative to on-board guidance and control (G&C) architectures for spacecraft, offering a differentiable, end-to-end rep…
Probability of collision in nonlinear dynamics by moment propagation
Théo Verhelst, Giacomo Acciarini, Dario Izzo +1
Estimating the probability of collision between spacecraft is crucial for risk management and collision-avoidance strategies. Current methods often rely on Gaussian assumptions and…
EclipseNETs: Learning Irregular Small Celestial Body Silhouettes
Giacomo Acciarini, Dario Izzo, Francesco Biscani
Accurately predicting eclipse events around irregular small bodies is crucial for spacecraft navigation, orbit determination, and spacecraft systems management. This paper introduc…
High-order expansion of Neural Ordinary Differential Equations flows
Dario Izzo, Sebastien Origer, Giacomo Acciarini +1
Artificial neural networks, widely recognised for their role in machine learning, are now transforming the study of ordinary differential equations (ODEs), bridging data-driven mod…
Certifying Guidance & Control Networks: Uncertainty Propagation to an Event Manifold
Sebastien Origer, Dario Izzo, Giacomo Acciarini +4
We perform uncertainty propagation on an event manifold for Guidance & Control Networks (G&CNETs), aiming to enhance the certification tools for neural networks in this field. This…