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Asteroids

Deep Reinforcement Learning - Based Policy for Autonomous Planning of Small Celestial Bodies Mapping
This paper deals with the problem of mapping unknown small celestial bodies while autonomously navigating in their proximity with an …
Margherita Piccinin, Paolo Lunghi, Michèle Lavagna
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Small Bodies Non-Uniform Gravity Field On-Board Learning through Hopfield Neural Networks
Small bodies environment is usually difficult to be modelled for a number of reasons. Among the others, the uncertainty associated to …
Andrea Pasquale, Stefano Silvestrini, Andrea Capannolo, Paolo Lunghi, Michèle Lavagna
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Optimal Configurations for Nanosatellite Formation Flying in Binary Asteroid Environment
The exploration of NEA (Near Earth Asteroids) is characterized by many problematics such as collision risks, irregular gravity fields …
Andrea Capannolo, Michèle Lavagna, Fabio Ferrari, Paolo Lunghi
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Hazard Detection and Avoidance Systems for Autonomous Planetary Landing
Precise and autonomous landing capability is a key feature for the next space systems generation. The possibility to carry out Hazard …
Paolo Lunghi
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Nanosatellite Formation Flying to Enhance Science in Binary Asteroid Environment
In the recent years, nanosatellites based missions are becoming of great interest in the space programs panorama, since they offer the …
Andrea Capannolo, Michèle Lavagna, Fabio Ferrari, Paolo Lunghi
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A Semi-Analytical Guidance Algorithm for Autonomous Landing
One of the main challenges posed by the next space systems generation is the high level of autonomy they will require. Hazard Detection …
Paolo Lunghi, Michèle Lavagna, Roberto Armellin
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Semi-Analytical Guidance Algorithm for Autonomous Close Approach to Non-Cooperative Low-Gravity Targets
Paolo Lunghi, Michèle Lavagna, Roberto Armellin
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