Zobrazeno 1 - 10
of 820
pro vyhledávání: '"Armellin A."'
The optimal design of multi-target rendezvous and flyby missions presents significant challenges due to their inherent combination of traditional spacecraft trajectory optimization with high-dimensional combinatorial problems. This often necessitates
Externí odkaz:
http://arxiv.org/abs/2411.11281
Autor:
Armellin, Roberto, Bellome, Andrea, Fu, Xiaoyu, Holt, Harry, Parigini, Cristina, Wijayatunga, Minduli, Yarndley, Jack
We present the solution approach developed by the team `TheAntipodes' during the 12th edition of the Global Trajectory Optimization Competition (GTOC 12). An overview of the approach is as follows: (1) generate asteroid subsets, (2) chain building wi
Externí odkaz:
http://arxiv.org/abs/2411.11279
Observability of the target, safety, and robustness are often recognized as critical factors in ensuring successful far-range proximity operations. The application of angles-only (AO) navigation for proximity operations is often met with hesitancy du
Externí odkaz:
http://arxiv.org/abs/2411.01021
The optimization of fuel-optimal low-thrust collision avoidance maneuvers (CAMs) in scenarios involving multiple encounters between spacecraft is addressed. The optimization's objective is the minimization of the total fuel consumption while respecti
Externí odkaz:
http://arxiv.org/abs/2406.03654
A simple and reliable algorithm for collision avoidance maneuvers (CAMs), capable of computing impulsive, multi-impulsive, and low-thrust maneuvers, is proposed. The probability of collision (PoC) is approximated by a polynomial of arbitrary order as
Externí odkaz:
http://arxiv.org/abs/2406.01949
A multifidelity method for the nonlinear propagation of uncertainties in the presence of stochastic accelerations is presented. The proposed algorithm treats the uncertainty propagation (UP) problem by separating the propagation of the initial uncert
Externí odkaz:
http://arxiv.org/abs/2405.15993
A convex optimization-based model predictive control (MPC) algorithm for the guidance of active debris removal (ADR) missions is proposed in this work. A high-accuracy reference for the convex optimization is obtained through a split-Edelbaum approac
Externí odkaz:
http://arxiv.org/abs/2311.10973
Autor:
Silvia Barbon, Fabrizio Armellin, Verena Passerini, Sergio De Angeli, Simona Primerano, Laura Del Pup, Elisabetta Durante, Veronica Macchi, Raffaele De Caro, Pier Paolo Parnigotto, Arianna Veronesi, Andrea Porzionato
Publikováno v:
Cell Communication and Signaling, Vol 22, Iss 1, Pp 1-19 (2024)
Abstract Background COVID-19 pandemic caused by the Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) represents the biggest global health emergency in recent decades. The host immune response to SARS-CoV-2 seems to play a key role in dise
Externí odkaz:
https://doaj.org/article/20aad837dc844546b30727688888e257
Publikováno v:
Preprint AAS 2023, Big Sky, Montana
Active debris removal (ADR) missions have garnered significant interest as means of mitigating collision risks in space. This work proposes a convex optimization-based model predictive control (MPC) approach to provide guidance for such missions. Whi
Externí odkaz:
http://arxiv.org/abs/2308.08783
This work presents a sequential convex program method to compute fuel-optimal collision avoidance maneuvers for long-term encounters. The low-thrust acceleration model is used to account for the control, but the method can compute high-thrust maneuve
Externí odkaz:
http://arxiv.org/abs/2307.06004