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Spacecraft autonomy

Investigation of Low-Energy Spiking Neural Networks Based on Temporal Coding for Scene Classification
Spiking Neural Networks (SNN) are becoming increasingly interesting to the space domain due to their energy efficiency. Indeed, small …
Paolo Lunghi, Stefano Silvestrini, Dominik Dold, Gabriele Meoni, Alexander Hadjiivanov, Dario Izzo
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Ariadna final presentation
The project results were presented at ESA/ESTEC.
Paolo Lunghi
Sep 25, 2023 1 min read Talks
Project Slides
Ariadna final presentation
Semi-Analytical Adaptive Guidance Computation for Autonomous Planetary Landing
A novel algorithm for autonomous landing guidance computation is presented. The trajectory is expressed in polynomial form of minimum …
Paolo Lunghi, Pierluigi Di Lizia, Roberto Armellin, Michèle Lavagna
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Ariadna - Spiking Neural Networks
Investigation of low energy Spiking Neural Networks based on temporal coding for scene classification
External Link Final report
Ariadna - Spiking Neural Networks
Advancements of Vision-Based Autonomous Planetary Landing Systems and Preliminary Testing by Means of a New Dedicated Experimental Facility
In this paper, a suite of tools and algorithms devoted to optical navigation for autonomous landing on planets and small bodies, …
Marco Ciarambino, Paolo Lunghi, Luca Losi, Michèle Lavagna
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Semi-Analytical Adaptive Guidance Computation Based on Differential Algebra for Autonomous Planetary Landing
A novel algorithm for autonomous landing guidance computation is presented. Trajectory is expressed in polynomial form of minimum order …
Paolo Lunghi, Roberto Armellin, Pierluigi Di Lizia, Michèle Lavagna
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Model Predictive Control for Relative GNC during Planetary Sample Canister Rendez-Vous and Capture Phase
This work presents a Guidance Navigation and Control (GNC) model to manage the rendezvous phase of an active spacecraft with an …
Michèle Lavagna, Vincenzo Campanelli, Paolo Lunghi
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