Charging strategies for electrostatic control of spacecraft formations

Formation control by means of electrostatic forces, generating attractive or repulsive actions by charging the satellites’ surfaces, has been recently proposed for high altitude orbits to precisely maintain the configuration without risk of plume impingement. This paper focuses on electrostatic control and switching strategies for charge distribution in spacecraft formations, taking into account the limits on the power requirements. Two nonlinear global control approaches are presented and applied to two and three satellites’ formations. Then, an optimized charge distribution process among the satellites is discussed and applied to the three spacecraft formation case. Numerical simulations are performed in order to evaluate the advantages and drawbacks of this configuration control technique

Design of the radiation shielding for a microsatellite

This paper aims to provide a detailed description of the problems concerning the radiation environment faced while designing a microsatellite at the University of Rome. Although main features of the microsatellite, as well as the environment characteristics expected in candidate orbits are detailed, emphasis is given to expose a generally appropriate procedure for this class of spacecraft. The sector analysis is carried on. and a simple qualitative way to point out critical areas of shielding is shown. The risk concerning the specific devices is assessed, both for total ionization dose and single event upset. The effect of the spot shielding on the most sensitive devices is considered, in order to mitigate SEE occurrence. (C) 2002 International Astronautical Federation. Published by Elsevier Science Ltd. All rights reserved

Virtual and rapid prototyping of an underactuated space end effector

A fast and reliable verification of an initial concept is an important need in the field of mechatronics. Usually, the steps for a successful design require multiple iterations involving a sequence of design phases-the initial one and several improvements-and the tests of the resulting prototypes, in a trial and error scheme. Now a day’s software and hardware tools allow for a faster approach, in which the iterations between design and prototyping are by far reduced, even to just one in favorable situation. This work presents the design, manufacturing and testing of a robotic end effector for space applications, realized through virtual prototyping, followed by rapid prototyping realization. The first process allows realizing a mathematical model of the robotic system that, once all the simulations confirm the effectiveness of the design, can be directly used for the rapid prototyping by means of 3D printing. The workflow and the results of the process are described in detail in this paper, showing the qualitative and quantitative evaluation of the performance of both the virtual end effector and the actual physical robotic hand

Debris Cloud Evolution: Mathematical Modeling and Application to Satellite Constellation Design

Orbital break-ups produce a large number of fragments, which constitute an obvious hazard for other satellites in nearby orbits. Of these fragments, many are too small to be detected by ground-based facilities: this leads to the need for mathematical modelling as a tool for adequate risk analysis. In this paper an average spatial density model is presented. It is based on the Gauss analogy and, for unperturbed Keplerian orbits, it matches the asymptotic density model developed by other authors. Risk analysis for satellite constellations is an interesting application of debris cloud evolution models: the survivability of a constellation as a whole following the break-up of one of its satellites is obviously of primary concern in the constellation design. Risk analysis is conducted over a number of traditional configurations in order to achieve an additional constraint on the design parameters. Results indicate the remarkable influence of the fragmentation point position along the orbit; moreover, the higher risk for low orbit and the advantage of placing more satellites on a limited number of planes are assessed

MEMS-based Inertial Navigation Systems onboard Balloons

Performances of low-cost inertial navigation sensors, usually poor, can often match different mission requirements by means of a careful signal and data processing and/or an augmentation by means of different observables. The paper presents the LOWCOINS navigation experiment, intended to fly onboard BEXUS balloon mission in late 2008. LOWCOINS has as the main component a low-cost three-axes inertial unit, integrating three accelerometers and three gyros. The slow dynamic typical of a balloon flight is deemed as an ideal test to verify the performances of the unit and to improve the knowledge on the data processing needed to obtain an accurate final navigation solution. In order to enlarge the set of available data, a cluster of magnetometers and a pressure sensor, always belonging to low-cost instrumentation range, are hosted on board. Measurements are both stored on board and downlinked to a ground station. Position and velocity components (both the onboard computed first guess and the post-flight calibrated solution) will be compared with the data gathered by a GPS receiver, which is a standard component of BEXUS balloon avionics. Substantial attention to thermal aspects has been requested in order to cope with environmental conditions prior of and all along the flight. The requested navigation unit case design is shortly reported

Intelligenza artificiale e sicurezza: opportunità, rischi e raccomandazioni

L'IA (o intelligenza artificiale) è una disciplina in forte espansione negli ultimi anni e lo sarà sempre più nel prossimo futuro: tuttavia è dal 1956 che l’IA studia l’emulazione dell’intelligenza da parte delle macchine, intese come software e in certi casi hardware. L’IA è nata dall’idea di costruire macchine che - ispirandosi ai processi legati all’intelligenza umana - siano in grado di risolvere problemi complessi, per i quali solitamente si ritiene che sia necessario un qualche tipo di ragionamento intelligente. La principale area di ricerca e applicazione attuale dell’IA è il machine learning (algoritmi che imparano e si adattano in base ai dati che ricevono), che negli ultimi anni ha trovato ampie applicazioni grazie alle reti neurali (modelli matematici composti da neuroni artificiali) che a loro volta hanno consentito la nascita del deep learning (reti neurali di maggiore complessità). Appartengono al mondo dell’IA anche i sistemi esperti, la visione artificiale, il riconoscimento vocale, l’elaborazione del linguaggio naturale, la robotica avanzata e alcune soluzioni di cybersecurity. Quando si parla di IA c'è chi ne è entusiasta pensando alle opportunità, altri sono preoccupati poiché temono tecnologie futuristiche di un mondo in cui i robot sostituiranno l'uomo, gli toglieranno il lavoro e decideranno al suo posto. In realtà l'IA è ampiamente utilizzata già oggi in molti campi, ad esempio nei cellulari, negli oggetti smart (IoT), nelle industry 4.0, per le smart city, nei sistemi di sicurezza informatica, nei sistemi di guida autonoma (drive o parking assistant), nei chat bot di vari siti web; questi sono solo alcuni esempi basati tutti su algoritmi tipici dell’intelligenza artificiale. Grazie all'IA le aziende possono avere svariati vantaggi nel fornire servizi avanzati, personalizzati, prevedere trend, anticipare le scelte degli utenti, ecc. Ma non è tutto oro quel che luccica: ci sono talvolta problemi tecnici, interrogativi etici, rischi di sicurezza, norme e legislazioni non del tutto chiare. Le organizzazioni che già adottano soluzioni basate sull’IA, o quelle che intendono farlo, potrebbero beneficiare di questa pubblicazione per approfondirne le opportunità, i rischi e le relative contromisure. La Community for Security del Clusit si augura che questa pubblicazione possa fornire ai lettori un utile quadro d’insieme di una realtà, come l’intelligenza artificiale, che ci accompagnerà sempre più nella vita personale, sociale e lavorativa.AI (or artificial intelligence) is a booming discipline in recent years and will be increasingly so in the near future.However, it is since 1956 that AI has been studying the emulation of intelligence by machines, understood as software and in some cases hardware. AI arose from the idea of building machines that-inspired by processes related to human intelligence-are able to solve complex problems, for which it is usually believed that some kind of intelligent reasoning is required. The main current area of AI research and application is machine learning (algorithms that learn and adapt based on the data they receive), which has found wide applications in recent years thanks to neural networks (mathematical models composed of artificial neurons), which in turn have enabled the emergence of deep learning (neural networks of greater complexity). Also belonging to the AI world are expert systems, computer vision, speech recognition, natural language processing, advanced robotics and some cybersecurity solutions. When it comes to AI there are those who are enthusiastic about it thinking of the opportunities, others are concerned as they fear futuristic technologies of a world where robots will replace humans, take away their jobs and make decisions for them. In reality, AI is already widely used in many fields, for example, in cell phones, smart objects (IoT), industries 4.0, for smart cities, cybersecurity systems, autonomous driving systems (drive or parking assistant), chat bots on various websites; these are just a few examples all based on typical artificial intelligence algorithms. Thanks to AI, companies can have a variety of advantages in providing advanced, personalized services, predicting trends, anticipating user choices, etc. But not all that glitters is gold: there are sometimes technical problems, ethical questions, security risks, and standards and legislation that are not entirely clear. Organizations already adopting AI-based solutions, or those planning to do so, could benefit from this publication to learn more about the opportunities, risks, and related countermeasures. Clusit's Community for Security hopes that this publication will provide readers with a useful overview of a reality, such as artificial intelligence, that will increasingly accompany us in our personal, social and working lives

Coordinated Orbit Control for Satellite Constellations and Formations

The paper deals with the optimal (in the propellant consumption respect) control of satellite constellations. Different approach to identify the best strategy, also with respect to time scheduling costraints, are presented and discussed

Capabilities of the GNSS Precise Point Positioning Technique for Landslide Monitoring

Global Navigation Satellite Systems signals are currently used in monitoring very slow changes in significant natural features which are potentially risky or worth of a careful attention, like incoming landslides, sites of subsidence, glaciers. This activity is generally carried out by exploiting the differences among the signals received at several sites and by making use of the phase observable of GNSS signals. This study is intended to shortly highlight the capabilities of a novel technique, the precise point positioning, which does not require the difference operation and still based on the signal phase, leads to accurate, simpler and cost effective measurements relevant to a single specific location. Precise point positioning has the potential to become a faster and cheaper technique to monitor landslide and slope failures phenomena, extending the interest also to not-too-large scale natural threats and geo-hazards and limit, by prompt alert, the risk of the associated catastrophic events