Artificial Intelligence for Small Satellites Mission Autonomy

Space mission engineering has always been recognized as a very challenging and innovative branch of engineering: since the beginning of the space race, numerous milestones, key successes and failures, improvements, and connections with other engineering domains have been reached. Despite its relative young age, space engineering discipline has not gone through homogeneous times: alternation of leading nations, shifts in public and private interests, allocations of resources to different domains and goals are all examples of an intrinsic dynamism that characterized this discipline. The dynamism is even more striking in the last two decades, in which several factors contributed to the fervour of this period. Two of the most important ones were certainly the increased presence and push of the commercial and private sector and the overall intent of reducing the size of the spacecraft while maintaining comparable level of performances. A key example of the second driver is the introduction, in 1999, of a new category of space systems called CubeSats. Envisioned and designed to ease the access to space for universities, by standardizing the development of the spacecraft and by ensuring high probabilities of acceptance as piggyback customers in launches, the standard was quickly adopted not only by universities, but also by agencies and private companies. CubeSats turned out to be a disruptive innovation, and the space mission ecosystem was deeply changed by this. New mission concepts and architectures are being developed: CubeSats are now considered as secondary payloads of bigger missions, constellations are being deployed in Low Earth Orbit to perform observation missions to a performance level considered to be only achievable by traditional, fully-sized spacecraft. CubeSats, and more in general the small satellites technology, had to overcome important challenges in the last few years that were constraining and reducing the diffusion and adoption potential of smaller spacecraft for scientific and technology demonstration missions. Among these challenges were: the miniaturization of propulsion technologies, to enable concepts such as Rendezvous and Docking, or interplanetary missions; the improvement of telecommunication state of the art for small satellites, to enable the downlink to Earth of all the data acquired during the mission; and the miniaturization of scientific instruments, to be able to exploit CubeSats in more meaningful, scientific, ways. With the size reduction and with the consolidation of the technology, many aspects of a space mission are reduced in consequence: among these, costs, development and launch times can be cited. An important aspect that has not been demonstrated to scale accordingly is operations: even for small satellite missions, human operators and performant ground control centres are needed. In addition, with the possibility of having constellations or interplanetary distributed missions, a redesign of how operations are management is required, to cope with the innovation in space mission architectures. The present work has been carried out to address the issue of operations for small satellite missions. The thesis presents a research, carried out in several institutions (Politecnico di Torino, MIT, NASA JPL), aimed at improving the autonomy level of space missions, and in particular of small satellites. The key technology exploited in the research is Artificial Intelligence, a computer science branch that has gained extreme interest in research disciplines such as medicine, security, image recognition and language processing, and is currently making its way in space engineering as well. The thesis focuses on three topics, and three related applications have been developed and are here presented: autonomous operations by means of event detection algorithms, intelligent failure detection on small satellite actuator systems, and decision-making support thanks to intelligent tradespace exploration during the preliminary design of space missions. The Artificial Intelligent technologies explored are: Machine Learning, and in particular Neural Networks; Knowledge-based Systems, and in particular Fuzzy Logics; Evolutionary Algorithms, and in particular Genetic Algorithms. The thesis covers the domain (small satellites), the technology (Artificial Intelligence), the focus (mission autonomy) and presents three case studies, that demonstrate the feasibility of employing Artificial Intelligence to enhance how missions are currently operated and designed

DESIGN AND ANALYSIS OF AN INNOVATIVE CUBESAT THERMAL CONTROL SYSTEM FOR BIOLOGICAL EXPERIMENT IN LUNAR ENVIRONMENT

After about 50 years since the Apollo missions, Space Agencies are planning new manned missions beyond LEO, aiming to full functional Lunar and Martian outposts. Leaving the protection of Earth’s magnetic field, human body will be exposed by a huge amount of harmful radiations coming from both solar wind and cosmic rays, which represent a risk for the astronauts. In order to prepare for future manned exploration missions, many biological experiments have been conducted inside and outside the International Space Station (ISS). From these experiments, engineers and scientists gained knowledge about biological degradation after a long period of exposure to space radiations. Similar experiments were also carried out in small free-flyers. For example, the O/OREOS mission is built with a 3U CubeSat that is evaluating how microorganisms can survive and can adapt to the harsh orbit environment. Small platforms, such as CubeSats, are gaining interest for many applications including science experiments. Biological payloads require very stable environmental conditions, implying that environment requirements are very stringent and that existing passive thermal control systems may not be sufficient to support these class of experiments. The goal of this paper is to describe and discuss the design of an active environmental control system suitable for supporting biological payloads hosted onboard nanosatellites. In particular, we focused the attention on the case of a payload constituted by a bacterial culture that needs oxygen supply for growing up. The rate of growth and vitality are measured through bacteria metabolic parameters. The reference mission is built with a 6U CubeSat in Lunar Polar Orbit, with the main scientific objective of measuring the effect of the lunar radiation environment on a culture of “Bacterium Deinococcus Radiodurans”. This kind of bacteria exhibits significant resistance to ionising radiation and the survival temperature range is 30°C ± 10°C. The thermal control system (TCS) is constituted by Stirling cryocooler, Peltier cells and heaters. The aforementioned pieces of equipment operate on the oxygen tank and test chamber in order to control temperature of the oxygen necessary for the growth of the bacteria. To verify the temperature requirements, two kinds of analysis are performed: radiative analysis, to have information about the heat fluxes from space environment; and lastly, a thermo-fluid dynamics analysis, to gather data about temperature in the test chamber. As result, it is possible to confirm that, with the chosen TCS, the temperature requirement is verified during the mission

Application of nanosatellites for lunar missions

Two major themes for the space sector in recent years have been the resurgence of missions to the Moon, facilitating the expansion of human presence into the Solar System, and the rapid growth in CubeSat launches. Lunar missions will play an important role in sustainable space exploration, as discussed in the Global Exploration Roadmap. The Roadmap outlines the next steps for the current and next generation of explorers and reaffirms the interest of 14 space agencies to return to the Moon. Over the past decade, a more daring approach to space innovation and the proliferation of low-cost small satellites have invited commercialization and, subsequently, have accelerated the development of miniaturized technologies and substantially reduced the costs associated with CubeSats. In this context, CubeSats are increasingly being considered as platforms for pioneering missions beyond low-Earth orbit. This paper describes a 3U nanosatellite mission to the Moon, designed as part of the UKSEDS Satellite Design Competition, capable of capturing and analysing details of the lunar environment. To achieve the primary mission objectives, a camera and an infrared spectrometer have been included to relay information about historic lunar landmarks to Earth. The design was developed to be integrated with Open Cosmos' OpenKit and reviewed by experts in the field from SSPI. The paper includes a detailed assessment of the current state of miniaturized instruments and the quality of scientific return which can be achieved by a lunar CubeSat mission. This concludes in an overall feasibility study of lunar CubeSats, a discussion of the current limitations and challenges associated with CubeSat technologies and a framework for future missions

1U CubeSatでのバイナリ画像分類用に設計された畳み込みニューラルネットワーク

As of 2020, more than a thousand CubeSats have been launched into space. The nanosatellite standard allowed launch providers to utilize empty spaces in their rockets while giving educational institutions, research facilities and commercial start-up companies the chance to build, test and operate satellites in orbit. This exponential rise in the number of CubeSats has led to an increasing number of diverse missions. Missions on astrobiology, state-of-art technology demonstration, high revisit-time earth observation and space weather have been implemented. In 2018, NASA’s JPL demonstrated CubeSat’s first use in deep space by launching MarCO A and MarCO B. The CubeSats successfully relayed information received from InSight Mars Lander in Mars to Earth. Increasing complexity in missions, however, require increased access to data. Most CubeSats still rely on extremely low data rates for data transfer. Size, Weight and Power (SWaP) requirements for 1U are stringent and rely on VHF/UHF bands for data transmission. Kyushu Institute of Technology’s BIRDS-3 Project has downlink rate of 4800bps and takes about 2-3 days to reconstruct a 640x480 (VGA) image on the ground. Not only is this process extremely time consuming and manual but it also does not guarantee that the image downlinked is usable. There is a need for automatic selection of quality data and improve the work process. The purpose of this research is to design a state-of-art, novel Convolutional Neural Network (CNN) for automated onboard image classification on CubeSats. The CNN is extremely small, efficient, accurate, and versatile. The CNN is trained on a completely new CubeSat image dataset. The CNN is designed to fulfill SWaP requirements of 1U CubeSat so that it can be scaled to fit in bigger satellites in the future. The CNN is tested on never-before-seen BIRDS-3 CubeSat test dataset and is benchmarked against SVM, AE and DBN. The CNN automatizes images selection on-orbit, prioritizes quality data, and cuts down operation time significantly.九州工業大学博士学位論文 学位記番号：工博甲第510号 学位授与年月日：令和2年12月28日1 Introduction|2 Convolutional Neural Networks|3 Methodology|4 Results|5 Conclusion九州工業大学令和2年

The State of the Art of Information Integration in Space Applications

This paper aims to present a comprehensive survey on information integration (II) in space informatics. With an ever-increasing scale and dynamics of complex space systems, II has become essential in dealing with the complexity, changes, dynamics, and uncertainties of space systems. The applications of space II (SII) require addressing some distinctive functional requirements (FRs) of heterogeneity, networking, communication, security, latency, and resilience; while limited works are available to examine recent advances of SII thoroughly. This survey helps to gain the understanding of the state of the art of SII in sense that (1) technical drivers for SII are discussed and classified; (2) existing works in space system development are analyzed in terms of their contributions to space economy, divisions, activities, and missions; (3) enabling space information technologies are explored at aspects of sensing, communication, networking, data analysis, and system integration; (4) the importance of first-time right (FTR) for implementation of a space system is emphasized, the limitations of digital twin (DT-I) as technological enablers are discussed, and a concept digital-triad (DT-II) is introduced as an information platform to overcome these limitations with a list of fundamental design principles; (5) the research challenges and opportunities are discussed to promote SII and advance space informatics in future

Nanosatelliide kasutamine demonstratsioon- ja teadusmissioonidel

Väitekirja elektrooniline versioon ei sisalda publikatsiooneKosmost on vaadeldud ja uuritud aastatuhandeid, kuid kosmosemissioonid lubasid seda esimest korda kohapeale uurima minna alles 64 aastat tagasi. Satelliidid võimaldavad teha toiminguid, mis maapealsete uuringutega on võimatud, näiteks maanduda teistele taevakehadele, tuua Maale neilt võetud proove vaadelda lähedalt komeete, ja asteroide ning saada paremaid vaatlusandmeid galaktikate, päikesesüsteemide, eksoplaneetide ja muude objektide kohta.. Ajalooliselt korraldasid kosmosemissioone suured riiklikud kosmoseagentuurid, kuid viimase 20 aasta jooksul on valdkond avanenud ka väikeettevõtetele, ülikoolidele ja pea kõigile teistele, kes on satelliidi kosmosesse saatmisest huvitatud. See on saanud võimalikuks tänu kuupsatelliitide standardiseerimisele. Tavaliselt peame kuupsatelliitide all silmas 1–10 kg nanosatelliite. Selle väitekirja autor on aidanud kaasa planeedimissioonide ja -instrumentide miniaturiseerimisele, töötades välja missioone ja missioonikontseptsioone ning arendades selliseid koormused ja simulatsioonivahendeid, mis aitaksid kaasa pikaajalisele eesmärgile uurida kosmost nanosatelliitidega. Lõputöö esimene osa keskendub uuenduslikule kosmosereiside tehnoloogiale: Coulomb Drag Propulsionile. Seda saab kasutada, et madalalt Maa orbiidilt kosmoseprügi eemaldada (plasmapidur) või kosmoses liikuda, kandmata Maalt kaasa võetud raketikütust (elektriline päiksepuri). Kõnealune tõukejõutehnoloogia on paigaldatud satelliitidele ESTCube-2 ja FORESAIL-1, mis peagi kosmosesse lennutatakse. Samuti analüüsib doktoritöö ideed külastada elektrilise päiksepurje juhitava kuupsatelliidilaevastikuga sadu asteroide. Lõputöö teises osas antakse ülevaade jätkuvast protsessist eesmärgiga arendada kaamera Euroopa Kosmoseagentuuri (ESA) ja Jaapani Kosmoseuuringute Agentuuri (JAXA) ellu viidavale Komeedipüüduri (Comet Interceptor) missioonile. Missiooni sondid viib 2029. aastal kosmosesse rakett Ariane 6. Kaamera on varustatud periskoobiga, et kaitsta seda ohtliku keskkonna eest, mistõttu kannab see nime Optical Periscopic Imager for Comets või OPIC. Nimi viitab ühtlasi Eesti astronoomile Ernst Öpikule, kes pakkus esimesena välja, et Päikesesüsteemi ümber asub kauge komeedipilv, mida tänapäeval tuntakse Öpiku–Oorti pilvena. OPIC-u väljatöötamist toetab spetsiaalselt selleks arendatud simulatsioonitööriist SISPO, mida kirjeldatakse doktoritöö viimases osas.Humans have been observing and exploring the cosmos for millennia, yet space missions enabled in-situ examination only during the last 64 years. Artificial satellites enable opportunities unfeasible for ground-based studies, such as landing on other planetary bodies, sample return, close observations of comets and asteroids, and improved observations of galaxies, solar systems, exoplanets, etc. Historically, space missions were operated by large space agencies, but in the last twenty years, the field expanded to small enterprises, universities and practically anyone interested in launching a satellite. This was partially enabled by the standardisation of cubesats, typically 1–10 kg nanosatellites. The author of this dissertation has contributed to the miniaturisation of planetary missions and instruments by developing missions, mission concepts, payloads and simulation tools that commit to the long-term aims of cosmic exploration with nanospacecraft. The first part of the thesis focuses on innovative technology for space travel – Coulomb Drag Propulsion. It can be utilised to remove space debris from Low Earth Orbit (named plasma brake) or travel in space without carrying the propellant from the Earth (named E-sail). This propulsion is accommodated on the ESTCube-2 and FORESAIL-1 satellites, to be launched soon. The dissertation also analyses the concept of visiting hundreds of asteroids with a fleet of cubesats driven by E-sail. The second part of the thesis presents an ongoing camera development for the ESA-JAXA Comet Interceptor mission to be launched in 2029 by the Ariane 6 rocket. The camera is equipped with a periscope to protect it from a hazardous environment. It is therefore named Optical Periscopic Imager for Comets or OPIC shortly, also referring to the Estonian astronomer Ernst Öpik, who was the first to propose the existence of a distant comet cloud around the Solar System, known today as the Öpik–Oort cloud. The development of the OPIC instrument is supported by a custom-made open-source simulation tool called SISPO, described in the last part.  https://www.ester.ee/record=b547253

畳み込みニューラルネットワークアプローチを使用した山火事検出のための宇宙イメージングの前処理と後処理

An increasing number of wildfire cases every year has caused fear around the world. Scientists and researchers agreed that this catastrophe occurred due to climate change. Dry and windy conditions had worsened the situation in the affected area. Properties and life losses have created serious concerns for the authority to find a solution for preparing and fighting the fire promptly. Since the late ‘70s, leveraging satellite technology has brought helpful insight to monitor, detect, and assess wildfire events. NOAA AVHRR is one of the oldest Earth Observation (EO) satellites with the main objective of detecting and mapping forest fires. The MODIS fire product regularly upgrades the sensor technology and launches the satellites into space. However, with the advancement of current technologies, a miniaturized satellite called CubeSat creates a novel mission design by reducing the satellite development time, increasing the launching batch in a constellation method, and enhancing the detection result wildfire. The prime limitations of CubeSat are the size, weight, and power (SWaP), which lead to the optimization design of the payload and the communication subsystem. The big image data acquired by the CubeSat creates a bottleneck effect between the satellite and the ground station due to the low downlink data rate. Deep learning (DL) techniques are improving in the computer vision area. Image classification, detection, and segmentation are used in neural network architecture designed by artificial intelligence researchers. In this study, the convolution neural network (CNN) algorithm was chosen for the pre-processing onboard CubeSat for wildfire detection as well as for the graphical user interface (GUI) used on the ground post-processing. The first and crucial step was to develop a custom dataset for wildfire images by leveraging satellite imagery. Defining the specifications of the CubeSat payload to which the CNN was implemented could support selecting the accurate resolution and bands for acquiring the satellite images. The KITSUNE satellite is a 6-unit CubeSat platform implementing the CNN onboard for wildfire image classification. It serves as the secondary mission to support the main mission of a 5-m class EO. The on-ground testing revealed that the CNN could classify wildfire occurrences on the satellite system using the MiniVGGNet network with an overall accuracy of 98 % and an F1-score of 97% success rate in 137 seconds. Other models were also compared, such as ResNet and MiniGoogLeNet implemented on the GUI with 97% and 96% F1-score, respectively. Overall, this research showed the feasibility of CubeSat of executing CNN onboard in orbit, particularly for wildfire detection.九州工業大学博士学位論文 学位記番号：工博甲第556号 学位授与年月日：令和4年9月26日1: Introduction|2: Research Background and Literature Reviews|3: Research Methodology|4: Results|5: Discussion|6: Conclusion and Recommendation九州工業大学令和4年

Direct Multipixel Imaging and Spectroscopy of an Exoplanet with a Solar Gravity Lens Mission

We examined the solar gravitational lens (SGL) as the means to produce direct high-resolution, multipixel images of exoplanets. The properties of the SGL are remarkable: it offers maximum light amplification of ~1e11 and angular resolution of ~1e-10 arcsec. A probe with a 1-m telescope in the SGL focal region can image an exoplanet at 30 pc with 10-kilometer resolution on its surface, sufficient to observe seasonal changes, oceans, continents, surface topography. We reached and exceeded all objectives set for our study: We developed a new wave-optical approach to study the imaging of exoplanets while treating them as extended, resolved, faint sources at large but finite distances. We properly accounted for the solar corona brightness. We developed deconvolution algorithms and demonstrated the feasibility of high-quality image reconstruction under realistic conditions. We have proven that multipixel imaging and spectroscopy of exoplanets with the SGL are feasible. We have developed a new mission concept that delivers an array of optical telescopes to the SGL focal region relying on three innovations: i) a new way to enable direct exoplanet imaging, ii) use of smallsats solar sails fast transit through the solar system and beyond, iii) an open architecture to take advantage of swarm technology. This approach enables entirely new missions, providing a great leap in capabilities for NASA and the greater aerospace community. Our results are encouraging as they lead to a realistic design for a mission that will be able to make direct resolved images of exoplanets in our stellar neighborhood. It could allow exploration of exoplanets relying on the SGL capabilities decades, if not centuries, earlier than possible with other extant technologies. The architecture and mission concepts for a mission to the strong interference region of the SGL are promising and should be explored further