A comparative analysis of algorithms for satellite operations scheduling

Scheduling is employed in everyday life, ranging from meetings to manufacturing and operations among other activities. One instance of scheduling in a complex real-life setting is space mission operations scheduling, i.e. instructing a satellite to perform fitting tasks during predefined time periods with a varied frequency to achieve its mission goals. Mission operations scheduling is pivotal to the success of any space mission, choreographing every task carefully, accounting for technological and environmental limitations and constraints along with mission goals.;It remains standard practice to this day, to generate operations schedules manually ,i.e. to collect requirements from individual stakeholders, collate them into a timeline, compare against feasibility and available satellite resources, and find potential conflicts. Conflict resolution is done by hand, checked by a simulator and uplinked to the satellite weekly. This process is time consuming, bears risks and can be considered sub-optimal.;A pertinent question arises: can we automate the process of satellite mission operations scheduling? And if we can, what method should be used to generate the schedules? In an attempt to address this question, a comparison of algorithms was deemed suitable in order to explore their suitability for this particular application.;The problem of mission operations scheduling was initially studied through literature and numerous interviews with experts. A framework was developed to approximate a generic Low Earth Orbit satellite, its environment and its mission requirements. Optimisation algorithms were chosen from different categories such as single-point stochastic without memory (Simulated Annealing, Random Search), multi-point stochastic with memory (Genetic Algorithm, Ant Colony System, Differential Evolution) and were run both with and without Local Search.;The aforementioned algorithmic set was initially tuned using a single 89-minute Low Earth Orbit of a scientific mission to Mars. It was then applied to scheduling operations during one high altitude Low Earth Orbit (2.4hrs) of an experimental mission.;It was then applied to a realistic test-case inspired by the European Space Agency PROBA-2 mission, comprising a 1 day schedule and subsequently a 7 day schedule - equal to a Short Term Plan as defined by the European Space Agency.;The schedule fitness - corresponding to the Hamming distance between mission requirements and generated schedule - are presented along with the execution time of each run. Algorithmic performance is discussed and put at the disposal of mission operations experts for consideration.Scheduling is employed in everyday life, ranging from meetings to manufacturing and operations among other activities. One instance of scheduling in a complex real-life setting is space mission operations scheduling, i.e. instructing a satellite to perform fitting tasks during predefined time periods with a varied frequency to achieve its mission goals. Mission operations scheduling is pivotal to the success of any space mission, choreographing every task carefully, accounting for technological and environmental limitations and constraints along with mission goals.;It remains standard practice to this day, to generate operations schedules manually ,i.e. to collect requirements from individual stakeholders, collate them into a timeline, compare against feasibility and available satellite resources, and find potential conflicts. Conflict resolution is done by hand, checked by a simulator and uplinked to the satellite weekly. This process is time consuming, bears risks and can be considered sub-optimal.;A pertinent question arises: can we automate the process of satellite mission operations scheduling? And if we can, what method should be used to generate the schedules? In an attempt to address this question, a comparison of algorithms was deemed suitable in order to explore their suitability for this particular application.;The problem of mission operations scheduling was initially studied through literature and numerous interviews with experts. A framework was developed to approximate a generic Low Earth Orbit satellite, its environment and its mission requirements. Optimisation algorithms were chosen from different categories such as single-point stochastic without memory (Simulated Annealing, Random Search), multi-point stochastic with memory (Genetic Algorithm, Ant Colony System, Differential Evolution) and were run both with and without Local Search.;The aforementioned algorithmic set was initially tuned using a single 89-minute Low Earth Orbit of a scientific mission to Mars. It was then applied to scheduling operations during one high altitude Low Earth Orbit (2.4hrs) of an experimental mission.;It was then applied to a realistic test-case inspired by the European Space Agency PROBA-2 mission, comprising a 1 day schedule and subsequently a 7 day schedule - equal to a Short Term Plan as defined by the European Space Agency.;The schedule fitness - corresponding to the Hamming distance between mission requirements and generated schedule - are presented along with the execution time of each run. Algorithmic performance is discussed and put at the disposal of mission operations experts for consideration

Rule-Based System Architecting of Earth Observing Systems: Earth Science Decadal Survey

This paper presents a methodology to explore the architectural trade space of Earth observing satellite systems, and applies it to the Earth Science Decadal Survey. The architecting problem is formulated as a combinatorial optimization problem with three sets of architectural decisions: instrument selection, assignment of instruments to satellites, and mission scheduling. A computational tool was created to automatically synthesize architectures based on valid combinations of options for these three decisions and evaluate them according to several figures of merit, including satisfaction of program requirements, data continuity, affordability, and proxies for fairness, technical, and programmatic risk. A population-based heuristic search algorithm is used to search the trade space. The novelty of the tool is that it uses a rule-based expert system to model the knowledge-intensive components of the problem, such as scientific requirements, and to capture the nonlinear positive and negative interactions between instruments (synergies and interferences), which drive both requirement satisfaction and cost. The tool is first demonstrated on the past NASA Earth Observing System program and then applied to the Decadal Survey. Results suggest that the Decadal Survey architecture is dominated by other more distributed architectures in which DESDYNI and CLARREO are consistently broken down into individual instruments."La Caixa" FoundationCharles Stark Draper LaboratoryGoddard Space Flight Cente

The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed

Rule-based system architecting of Earth observation satellite systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 399-412).System architecting is concerned with exploring the tradespace of early, high-level, system design decisions with a holistic, value-centric view. In the last few years, several tools and methods have been developed to support the system architecting process, focusing on the representation of an architecture as a set of interrelated decisions. These tools are best suited for applications that focus on breadth - i.e., enumerating a large and representative part of the architectural tradespace -as opposed to depth - modeling fidelity. However, some problems in system architecting require good modeling depth in order to provide useful results. In some cases, a very large body of expert knowledge is required. Current tools are not designed to handle such large bodies of knowledge because they lack scalability and traceability. As the size of the knowledge base increases, it becomes harder: a) to modify existing knowledge or add new knowledge; b) to trace the results of the tool to the model assumptions or knowledge base. This thesis proposes a holistic framework for architecture tradespace exploration of large complex systems that require a large body of expert knowledge. It physically separates the different bodies of knowledge required to solve a system architecting problem (i.e., knowledge about the domain, knowledge about the class of optimization or search problem, knowledge about the particular instance of problem) by using a rule-based expert system. It provides a generic population-based heuristic algorithm for search, which can be augmented with rules that encode knowledge about the domain, or about the optimization problem or class of problems. It identifies five major classes of system architecting problems from the perspective of optimization and search, and provides rules to enumerate architectures and search through the architectural tradespace of each class. A methodology is also defined to assess the value of an architecture using a rule-based approach. This methodology is based on a decomposition of stakeholder needs into requirements and a systematic comparison between system requirements and system capabilities using the rules engine. The framework is applied to the domain of Earth observing satellite systems (EOSS). Three EOSS are studied in depth: the NASA Earth Observing System, the NRC Earth Science Decadal Survey, and the Iridium GEOscan program. The ability of the framework to produce useful results is shown, and specific insights and recommendations are drawn.by Daniel Selva Valero.Ph.D

Approximate Path Searching Method for Single-Satellite Observation and Transmission Task Planning Problem

Satellite task planning not only plans the observation tasks to collect images of the earth surface, but also schedules the transmission tasks to download images to the ground station for users’ using, which plays an important role in improving the efficiency of the satellite observation system. However, most of the work to our knowledge, scheduling the observation and transmission tasks separately, ignores the correlation between them in resource (e.g., energy and memory) consumption and acquisition. In this paper, we study the single-satellite observation and transmission task planning problem under a more accurate resource usage model. Two preprocessing strategies including graph partition and nondominated subpaths selection are used to decompose the problem, and an improved label-setting algorithm with the lower bound cutting strategy is proposed to maximize the total benefit. Finally, we compare the proposed method with other three algorithms based on three data sets, and the experimental result shows that our method can find the near-optimal solution in much less time

Mission Planning Techniques for Cooperative LEO Spacecraft Constellations

This research develops a mission planning approach that allows different systems to cooperate in accomplishing a single mission goal. Using the techniques described allows satellites to cooperate in efficiently maneuvering, or collecting images of Earth and transmitting the collected data to users on the ground. The individual resources onboard each satellite, like fuel, memory capacity and pointing agility, are used in a manner that ensures the goals and objectives of the mission are realized in a feasible way. A mission plan can be generated for each satellite within the cooperating group that collectively optimize the mission objectives from a global viewpoint. The unique methods and framework presented for planning the spacecraft operations are flexible and can be applied to a variety of decision making processes where prior decisions impact later decision options. This contribution to the satellite constellation mission planning field, thus has greater applicability to the wider decision problem discipline

In pursuit of autonomous distributed satellite systems

A la pàgina 265 diu: "In an effort to facilitate the reproduction of results, both the source code of the simulation environment and the configuration files that were prepared for the design characterisation are available in an open repository: https://github.com/carlesaraguz/aeossSatellite imagery has become an essential resource for environmental, humanitarian, and industrial endeavours. As a means to satisfy the requirements of new applications and user needs, novel Earth Observation (EO) systems are exploring the suitability of Distributed Satellite Systems (DSS) in which multiple observation assets concurrently sense the Earth. Given the temporal and spatial resolution requirements of EO products, DSS are often envisioned as large-scale systems with multiple sensing capabilities operating in a networked manner. Enabled by the consolidation of small satellite platforms and fostered by the emerging capabilities of distributed systems, these new architectures pose multiple design and operational challenges. Two of them are the main pillars of this research, namely, the conception of decision-support tools to assist the architecting process of a DSS, and the design of autonomous operational frameworks based on decentralised, on-board decision-making. The first part of this dissertation addresses the architecting of heterogeneous, networked DSS architectures that hybridise small satellite platforms with traditional EO assets. We present a generic design-oriented optimisation framework based on tradespace exploration methodologies. The goals of this framework are twofold: to select the most optimal constellation design; and to facilitate the identification of design trends, unfeasible regions, and tensions among architectural attributes. Oftentimes in EO DSS, system requirements and stakeholder preferences are not only articulated through functional attributes (i.e. resolution, revisit time, etc.) or monetary constraints, but also through qualitative traits such as flexibility, evolvability, robustness, or resiliency, amongst others. In line with that, the architecting framework defines a single figure of merit that aggregates quantitative attributes and qualitative ones-the so-called ilities of a system. With that, designers can steer the design of DSS both in terms of performance or cost, and in terms of their high-level characteristics. The application of this optimisation framework has been illustrated in two timely use-cases identified in the context of the EU-funded ONION project: a system that measures ocean and ice parameters in Polar regions to facilitate weather forecast and off-shore operations; and a system that provides agricultural variables crucial for global management of water stress, crop state, and draughts. The analysis of architectural features facilitated a comprehensive understanding of the functional and operational characteristics of DSS. With that, this thesis continues to delve into the design of DSS by focusing on one particular functional trait: autonomy. The minimisation of human-operator intervention has been traditionally sought in other space systems and can be especially critical for large-scale, structurally dynamic, heterogeneous DSS. In DSS, autonomy is expected to cope with the likely inability to operate very large-scale systems in a centralised manner, to improve the science return, and to leverage many of their emerging capabilities (e.g. tolerance to failures, adaptability to changing structures and user needs, responsiveness). We propose an autonomous operational framework that provides decentralised decision-making capabilities to DSS by means of local reasoning and individual resource allocation, and satellite-to-satellite interactions. In contrast to previous works, the autonomous decision-making framework is evaluated in this dissertation for generic constellation designs the goal of which is to minimise global revisit times. As part of the characterisation of our solution, we stressed the implications that autonomous operations can have upon satellite platforms with stringent resource constraints (e.g. power, memory, communications capabilities) and evaluated the behaviour of the solution for a large-scale DSS composed of 117 CubeSat-like satellite units.La imatgeria per satèl·lit ha esdevingut un recurs essencial per assolir tasques ambientals, humanitàries o industrials. Per tal de satisfer els requeriments de les noves aplicacions i usuaris, els sistemes d’observació de la Terra (OT) estan explorant la idoneïtat dels Sistemes de Satèl·lit Distribuïts (SSD), on múltiples observatoris espacials mesuren el planeta simultàniament. Degut al les resolucions temporals i espacials requerides, els SSD sovint es conceben com sistemes de gran escala que operen en xarxa. Aquestes noves arquitectures promouen les capacitats emergents dels sistemes distribuïts i, tot i que són possibles gràcies a l’acceptació de les plataformes de satèl·lits petits, encara presenten molts reptes en quant al disseny i operacions. Dos d’ells són els pilars principals d’aquesta tesi, en concret, la concepció d’eines de suport a la presa de decisions pel disseny de SSD, i la definició d’operacions autònomes basades en gestió descentralitzada a bord dels satèl·lits. La primera part d’aquesta dissertació es centra en el disseny arquitectural de SSD heterogenis i en xarxa, imbricant tecnologies de petits satèl·lits amb actius tradicionals. Es presenta un entorn d’optimització orientat al disseny basat en metodologies d’exploració i comparació de solucions. Els objectius d’aquest entorn són: la selecció el disseny de constel·lació més òptim; i facilitar la identificació de tendències de disseny, regions d’incompatibilitat, i tensions entre atributs arquitecturals. Sovint en els SSD d’OT, els requeriments del sistema i l’expressió de prioritats no només s’articulen en quant als atributs funcionals o les restriccions monetàries, sinó també a través de les característiques qualitatives com la flexibilitat, l’evolucionabilitat, la robustesa, o la resiliència, entre d’altres. En línia amb això, l’entorn d’optimització defineix una única figura de mèrit que agrega rendiment, cost i atributs qualitatius. Així l’equip de disseny pot influir en les solucions del procés d’optimització tant en els aspectes quantitatius, com en les característiques dalt nivell. L’aplicació d’aquest entorn d’optimització s’il·lustra en dos casos d’ús actuals identificats en context del projecte europeu ONION: un sistema que mesura paràmetres de l’oceà i gel als pols per millorar la predicció meteorològica i les operacions marines; i un sistema que obté mesures agronòmiques vitals per la gestió global de l’aigua, l’estimació d’estat dels cultius, i la gestió de sequeres. L’anàlisi de propietats arquitecturals ha permès copsar de manera exhaustiva les característiques funcionals i operacionals d’aquests sistemes. Amb això, la tesi ha seguit aprofundint en el disseny de SSD centrant-se, particularment, en un tret funcional: l’autonomia. Minimitzar la intervenció de l’operador humà és comú en altres sistemes espacials i podria ser especialment crític pels SSD de gran escala, d’estructura dinàmica i heterogenis. En els SSD s’espera que l’autonomia solucioni la possible incapacitat d’operar sistemes de gran escala de forma centralitzada, que millori el retorn científic i que n’apuntali les seves propietats emergents (e.g. tolerància a errors, adaptabilitat a canvis estructural i de necessitats d’usuari, capacitat de resposta). Es proposa un sistema d’operacions autònomes que atorga la capacitat de gestionar els sistemes de forma descentralitzada, a través del raonament local, l’assignació individual de recursos, i les interaccions satèl·lit-a-satèl·lit. Al contrari que treballs anteriors, la presa de decisions autònoma s’avalua per constel·lacions que tenen com a objectius de missió la minimització del temps de revisita global.Postprint (published version

In pursuit of autonomous distributed satellite systems

Satellite imagery has become an essential resource for environmental, humanitarian, and industrial endeavours. As a means to satisfy the requirements of new applications and user needs, novel Earth Observation (EO) systems are exploring the suitability of Distributed Satellite Systems (DSS) in which multiple observation assets concurrently sense the Earth. Given the temporal and spatial resolution requirements of EO products, DSS are often envisioned as large-scale systems with multiple sensing capabilities operating in a networked manner. Enabled by the consolidation of small satellite platforms and fostered by the emerging capabilities of distributed systems, these new architectures pose multiple design and operational challenges. Two of them are the main pillars of this research, namely, the conception of decision-support tools to assist the architecting process of a DSS, and the design of autonomous operational frameworks based on decentralised, on-board decision-making. The first part of this dissertation addresses the architecting of heterogeneous, networked DSS architectures that hybridise small satellite platforms with traditional EO assets. We present a generic design-oriented optimisation framework based on tradespace exploration methodologies. The goals of this framework are twofold: to select the most optimal constellation design; and to facilitate the identification of design trends, unfeasible regions, and tensions among architectural attributes. Oftentimes in EO DSS, system requirements and stakeholder preferences are not only articulated through functional attributes (i.e. resolution, revisit time, etc.) or monetary constraints, but also through qualitative traits such as flexibility, evolvability, robustness, or resiliency, amongst others. In line with that, the architecting framework defines a single figure of merit that aggregates quantitative attributes and qualitative ones-the so-called ilities of a system. With that, designers can steer the design of DSS both in terms of performance or cost, and in terms of their high-level characteristics. The application of this optimisation framework has been illustrated in two timely use-cases identified in the context of the EU-funded ONION project: a system that measures ocean and ice parameters in Polar regions to facilitate weather forecast and off-shore operations; and a system that provides agricultural variables crucial for global management of water stress, crop state, and draughts. The analysis of architectural features facilitated a comprehensive understanding of the functional and operational characteristics of DSS. With that, this thesis continues to delve into the design of DSS by focusing on one particular functional trait: autonomy. The minimisation of human-operator intervention has been traditionally sought in other space systems and can be especially critical for large-scale, structurally dynamic, heterogeneous DSS. In DSS, autonomy is expected to cope with the likely inability to operate very large-scale systems in a centralised manner, to improve the science return, and to leverage many of their emerging capabilities (e.g. tolerance to failures, adaptability to changing structures and user needs, responsiveness). We propose an autonomous operational framework that provides decentralised decision-making capabilities to DSS by means of local reasoning and individual resource allocation, and satellite-to-satellite interactions. In contrast to previous works, the autonomous decision-making framework is evaluated in this dissertation for generic constellation designs the goal of which is to minimise global revisit times. As part of the characterisation of our solution, we stressed the implications that autonomous operations can have upon satellite platforms with stringent resource constraints (e.g. power, memory, communications capabilities) and evaluated the behaviour of the solution for a large-scale DSS composed of 117 CubeSat-like satellite units.La imatgeria per satèl·lit ha esdevingut un recurs essencial per assolir tasques ambientals, humanitàries o industrials. Per tal de satisfer els requeriments de les noves aplicacions i usuaris, els sistemes d’observació de la Terra (OT) estan explorant la idoneïtat dels Sistemes de Satèl·lit Distribuïts (SSD), on múltiples observatoris espacials mesuren el planeta simultàniament. Degut al les resolucions temporals i espacials requerides, els SSD sovint es conceben com sistemes de gran escala que operen en xarxa. Aquestes noves arquitectures promouen les capacitats emergents dels sistemes distribuïts i, tot i que són possibles gràcies a l’acceptació de les plataformes de satèl·lits petits, encara presenten molts reptes en quant al disseny i operacions. Dos d’ells són els pilars principals d’aquesta tesi, en concret, la concepció d’eines de suport a la presa de decisions pel disseny de SSD, i la definició d’operacions autònomes basades en gestió descentralitzada a bord dels satèl·lits. La primera part d’aquesta dissertació es centra en el disseny arquitectural de SSD heterogenis i en xarxa, imbricant tecnologies de petits satèl·lits amb actius tradicionals. Es presenta un entorn d’optimització orientat al disseny basat en metodologies d’exploració i comparació de solucions. Els objectius d’aquest entorn són: la selecció el disseny de constel·lació més òptim; i facilitar la identificació de tendències de disseny, regions d’incompatibilitat, i tensions entre atributs arquitecturals. Sovint en els SSD d’OT, els requeriments del sistema i l’expressió de prioritats no només s’articulen en quant als atributs funcionals o les restriccions monetàries, sinó també a través de les característiques qualitatives com la flexibilitat, l’evolucionabilitat, la robustesa, o la resiliència, entre d’altres. En línia amb això, l’entorn d’optimització defineix una única figura de mèrit que agrega rendiment, cost i atributs qualitatius. Així l’equip de disseny pot influir en les solucions del procés d’optimització tant en els aspectes quantitatius, com en les característiques dalt nivell. L’aplicació d’aquest entorn d’optimització s’il·lustra en dos casos d’ús actuals identificats en context del projecte europeu ONION: un sistema que mesura paràmetres de l’oceà i gel als pols per millorar la predicció meteorològica i les operacions marines; i un sistema que obté mesures agronòmiques vitals per la gestió global de l’aigua, l’estimació d’estat dels cultius, i la gestió de sequeres. L’anàlisi de propietats arquitecturals ha permès copsar de manera exhaustiva les característiques funcionals i operacionals d’aquests sistemes. Amb això, la tesi ha seguit aprofundint en el disseny de SSD centrant-se, particularment, en un tret funcional: l’autonomia. Minimitzar la intervenció de l’operador humà és comú en altres sistemes espacials i podria ser especialment crític pels SSD de gran escala, d’estructura dinàmica i heterogenis. En els SSD s’espera que l’autonomia solucioni la possible incapacitat d’operar sistemes de gran escala de forma centralitzada, que millori el retorn científic i que n’apuntali les seves propietats emergents (e.g. tolerància a errors, adaptabilitat a canvis estructural i de necessitats d’usuari, capacitat de resposta). Es proposa un sistema d’operacions autònomes que atorga la capacitat de gestionar els sistemes de forma descentralitzada, a través del raonament local, l’assignació individual de recursos, i les interaccions satèl·lit-a-satèl·lit. Al contrari que treballs anteriors, la presa de decisions autònoma s’avalua per constel·lacions que tenen com a objectius de missió la minimització del temps de revisita global

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments

COBE's search for structure in the Big Bang

The launch of Cosmic Background Explorer (COBE) and the definition of Earth Observing System (EOS) are two of the major events at NASA-Goddard. The three experiments contained in COBE (Differential Microwave Radiometer (DMR), Far Infrared Absolute Spectrophotometer (FIRAS), and Diffuse Infrared Background Experiment (DIRBE)) are very important in measuring the big bang. DMR measures the isotropy of the cosmic background (direction of the radiation). FIRAS looks at the spectrum over the whole sky, searching for deviations, and DIRBE operates in the infrared part of the spectrum gathering evidence of the earliest galaxy formation. By special techniques, the radiation coming from the solar system will be distinguished from that of extragalactic origin. Unique graphics will be used to represent the temperature of the emitting material. A cosmic event will be modeled of such importance that it will affect cosmological theory for generations to come. EOS will monitor changes in the Earth's geophysics during a whole solar color cycle