21 citations · 33 across the 19 of their papers we have counts for
20 papers
Continuous Learning of Gravity Field Irregularities Around Small Bodies via Neural Hamiltonian ODEs
Giacomo Acciarini, Dario Izzo
We propose to learn the unknown dynamics in the proximity of a small body directly from tracking data, representing them as a feed-forward neural network embedded in the system Ham…
The Maximum Initial Mass
Dario Izzo, Giacomo Acciarini
We introduce the maximum-initial-mass problem as a standalone optimal-control formulation for low-thrust trajectory design and analyze its structure within Pontryagin's framework.…
Pretrained Approximators for Low-Thrust Trajectory Cost and Reachability
Zhong Zhang, Giacomo Acciarini, Dario Izzo +2
Low-thrust trajectory design relies heavily on repeated evaluations of fuel consumption and transfer feasibility, which require expensive optimal control solutions. In this work, w…
Reachability for Low-Thrust Trajectories via Maximum Initial Mass
Giacomo Acciarini, Dario Izzo, Zhong Zhang
Reachability analysis plays a central role in low-thrust spacecraft trajectory optimization by identifying which target states can be achieved under constraints on time, thrust, an…
A practical guide to implementing zero-order-hold interplanetary trajectory legs
Dario Izzo, Harry Holt, Giacomo Acciarini +2
We study the practical implementation of zero-order-hold (ZOH) transcriptions for spacecraft trajectory optimisation, identifying a set of design principles that render them robust…
The Keplerian Traveling Salesperson Problem
Max Bannach, Giacomo Acciarini, Dario Izzo
We address a fundamental challenge in space mission design and space logistics: planning interplanetary trajectories for missions that must rendezvous with multiple bodies. Such mi…
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…
EclipseNETs: a differentiable description of irregular eclipse conditions
Giacomo Acciarini, Francesco Biscani, Dario Izzo
In the field of spaceflight mechanics and astrodynamics, determining eclipse regions is a frequent and critical challenge. This determination impacts various factors, including the…
Nonlinear Propagation of Non-Gaussian Uncertainties
Giacomo Acciarini, Nicola Baresi, David Lloyd +1
This paper presents a novel approach for propagating uncertainties in dynamical systems building on high-order Taylor expansions of the flow and moment-generating functions (MGFs).…
NeuralODEs for VLEO simulations: Introducing thermoNET for Thermosphere Modeling
Dario Izzo, Giacomo Acciarini, Francesco Biscani
We introduce a novel neural architecture termed thermoNET, designed to represent thermospheric density in satellite orbital propagation using a reduced amount of differentiable com…
Computing low-thrust transfers in the asteroid belt, a comparison between astrodynamical manipulations and a machine learning approach
Giacomo Acciarini, Laurent Beauregard, Dario Izzo
Low-thrust trajectories play a crucial role in optimizing scientific output and cost efficiency in asteroid belt missions. Unlike high-thrust transfers, low-thrust trajectories req…
Global Optimization for Trajectory Design via Invariant Manifolds in the Earth-Moon Circular Restricted Three-Body Problem
Flavio Tagliaferri, Emmanuel Blazquez, Giacomo Acciarini +1
This study addresses optimal impulsive trajectory design within the Circular Restricted Three-Body Problem (CR3BP), presenting a global optimization-based approach to identify mini…
Stochastic Continuation of Trajectories in the Circular Restricted Three-Body Problem via Differential Algebra
Giacomo Acciarini, Nicola Baresi, David J. B. Lloyd +1
Numerical continuation techniques are powerful tools that have been extensively used to identify particular solutions of nonlinear dynamical systems and enable trajectory design in…
Breaking traditions: introducing a surrogate Primer Vector in non Keplerian dynamics
Laurent Beauregard, Dario Izzo, Giacomo Acciarini
In this study, we investigate trajectories involving multiple impulses within the framework of a generic spacecraft dynamics. Revisiting the age-old query of "How many impulses?",…
Guidance and Control Networks with Periodic Activation Functions
Sebastien Origer, Dario Izzo
Inspired by the versatility of sinusoidal representation networks (SIRENs), we present a modified Guidance & Control Networks (G&CNETs) variant using periodic activation functions…
Closing the Gap Between SGP4 and High-Precision Propagation via Differentiable Programming
Giacomo Acciarini, Atılım Güneş Baydin, Dario Izzo
The Simplified General Perturbations 4 (SGP4) orbital propagation method is widely used for predicting the positions and velocities of Earth-orbiting objects rapidly and reliably.…