Dissertations / Theses on the topic 'Autonomous Spacecraft - Software Architecture'

Thesis (M.S. in Astronautical Engineering and Astronautical Engineer Degree)--Naval Postgraduate School, December 2006.
Thesis Advisor(s): Romano, Marcello. "December 2006." Description based on title screen as viewed on March 12, 2008. Includes bibliographical references (p. 125-127). Also available in print.

The Autonomous Multi-Agent Physically Interacting Spacecraft (AMPHIS) test bed examines the problem of multiple spacecraft interacting at close proximity. This thesis contributes to this on-going research by addressing the development of the software architecture for the AMPHIS spacecraft simulator robots and the implementation of a Light Detection and Ranging (LIDAR) unit to be used for state estimation and navigation of the prototype robot. The software modules developed include: user input for simple user tasking; user output for data analysis and animation; external data links for sensors and actuators; and guidance, navigation and control (GNC). The software was developed in the SIMULINK/MATLAB environment as a consistent library to serve as stand alone simulator, actual hardware control on the robot prototype, and any combination of the two. In particular, the software enables hardware-in-the-loop testing to be conducted for any portion of the system with reliable simulation of all other portions of the system. The modularity of this solution facilitates fast proof-of-concept validation for the GNC algorithms. Two sample guidance and control algorithms were developed and are demonstrated here: a Direct Calculus of Variation method, and an artificial potential function guidance method. State estimation methods are discussed, including state estimation from hardware sensors, pose estimation strategies from various vision sensors, and the implementation of a LIDAR unit for state estimation. Finally, the relative motion of the AMPHIS test bed is compared to the relative motion on orbit, including how to simulate the on-orbit behavior using Hill's equations.

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica
This dissertation presents a software architecture called the Distributed Software Architecture for Autonomous Robots (DSAAR), which is designed to provide the fast development and prototyping of multi-robot systems. The DSAAR building blocks allow engineers to focus on the behavioural model of robots and collectives. This architecture is of special interest in domains where several human, robot, and software agents have to interact continuously. Thus, fast prototyping and reusability is a must. DSAAR tries to cope with these requirements towards an advanced solution to the n-humans and m-robots problem with a set of design good practices and development tools. This dissertation will also focus on Human-Robot Interaction, mainly on the subject of teleoperation. In teleoperation human judgement is an integral part of the process, heavily influenced by the telemetry data received from the remote environment. So the speed in which commands are given and the telemetry data is received, is of crucial importance. Using the DSAAR architecture a teleoperation approach is proposed. This approach was designed to provide all entities present in the network a shared reality, where every entity is an information source in an approach similar to the distributed blackboard. This solution was designed to accomplish a real time response, as well as, the completest perception of the robots’ surroundings. Experimental results obtained with the physical robot suggest that the system is able to guarantee a close interaction between users and robot.

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.
Includes bibliographical references (p. 95-96).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
The theory, simulation, design, and construction of a radically new type of unmanned aerial vehicle (UAV) are discussed. The vehicle architecture is based on a commercially available non-autonomous flyer called the Vectron Blackhawk Flying Saucer. Due to its full body rotation, the craft is more inherently gyroscopically stable than other more common types of UAVs. This morphology was chosen because it has never before been made autonomous, so the theory, simulation, design, and construction were all done from fundamental principles as an example of original multi-level autonomous development.
by Jesse H.Z. Davis.
M.Eng.

Approved for public release; distribution is unlimited
There is currently a very strong interest among researchers in the fields of artificial intelligence and robotics in finding more effective means of linking high level symbolic computations relating to mission planning and control for autonomous vehicles to low level vehicle control software. The diversity exhibited by the many processes involved in such control has resulted in a number of proposals for a general software architecture intended to provide an efficient yet flexible framework for the organization and interaction of relevant software components. The Rational Behavior Model (RBM) has been developed with these requirements in mind and consists of three levels, called the Strategic, the Tactical, and the Execution levels, respectively. Each level reflects computations supporting the solution to the global control problem based on different abstraction mechanisms. The unique contribution of the RBM architecture is the idea of specifying different programming paradigms to realize each software level. Specifically, RBM uses rule-based programming for the Strategic level, thereby permitting field reconfiguration of missions by a mission specialist without reprogramming at lower levels. The Tactical level realizes vehicle behaviors as the methods of software objects programmed in an object-based language such as Ada. These behaviors are initiated by rule satisfaction at the Strategic level, thereby rationalizing their interaction. The Execution level is programmed in any imperative language capable of supporting efficient execution of real-time control of the underlying vehicle hardware.

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Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior
We propose in this work a software architecture for robotic boats intended to act in diverse aquatic environments, fully autonomously, performing telemetry to a base station and getting this mission to be accomplished. This proposal aims to apply within the project N-Boat Lab NatalNet DCA, which aims to empower a sailboat navigating autonomously. The constituent components of this architecture are the memory modules, strategy, communication, sensing, actuation, energy, security and surveillance, making these systems the boat and base station. To validate the simulator was developed in C language and implemented using the graphics API OpenGL resources, whose main results were obtained in the implementation of memory, performance and strategy modules, more specifically data sharing, control of sails and rudder and planning short routes based on an algorithm for navigation, respectively. The experimental results, shown in this study indicate the feasibility of the actual use of the software architecture developed and their application in the area of autonomous mobile robotics
Propomos neste trabalho uma arquitetura de software para barcos rob?ticos destinados a atuarem em ambientes aqu?ticos diversos, de forma totalmente aut?noma, realizando telemetria com uma esta??o-base e desta recebendo miss?es a serem realizadas. Tal proposta visa aplicar-se dentro do projeto N-Boat do laborat?rio Natalnet-DCA, que tem como objetivo principal capacitar um veleiro a navegar autonomamente. Os componentes constituintes dessa arquitetura s?o os m?dulos de mem?ria, estrat?gia, comunica??o, sensoriamento, atua??o, energia, seguran?a e supervis?o, formando estes os sistemas do barco e da esta??o-base. Para sua valida??o foi desenvolvido um simulador implementado na linguagem C e utilizando recursos da API gr?fica OpenGL, cujos principais resultados foram obtidos na implementa??o dos m?dulos de mem?ria, de atua??o e de estrat?gia, mais especificamente no compartilhamento de dados, no controle das velas e do leme e no planejamento de rotas curtas baseado em um algoritmo de navega??o, respectivamente. Os resultados dos experimentos realizados, mostrados no presente trabalho, indicam a viabilidade da utiliza??o real da arquitetura de software desenvolvida e sua aplica??o na ?rea da rob?tica m?vel aut?noma

I världen växer forskning på självgående fordon dagligen.Målet med detta projekt var att skapa ett självgåendefordon och utforska möjligheterna att använda infrarödareflektioner som navigeringsmetod och hur man kanuppnå distinkta mätvärden. Avhandlingen diskuterar ävenmöjligheterna att använda flera prototyper i en störreskala. Under projektets gång byggdes ett prototypfordonför att genomföra experimenten angående lämplighetenmed navigering via infrarött ljus. Tester med prototypenvisar att navigering via infrarött ljus är väldigt pålitligtunder kontrollerade omständigheter. Projektet utforskaräven hur hierarkisk mjukvaruarkitektur står sig mot heltlokal eller centraliserad mjukvaruarkitektur.
In the world, research on autonomous navigation vehicles(AGV) is growing by the day. The goal with this projectwas to create an AGV and explore the possibility of usinginfrared reflections as a navigational method and how toachieve distinct reflection measurements from a surface.The thesis also discusses the possibility of using severalunits on a larger scale. In the progress of the project, aprototype vehicle was built to conduct the experiments toidentify the suitability of infrared navigation. The testingof the prototype shows that navigation by IR can be veryreliable under controlled circumstances. The project alsoexplored how hierarchical software architecture stands incomparison to purely local or centralized software architecture.

In the world, research on autonomous navigation vehicles (AGV) is growing by the day. The goal with this project was to create an AGV and explore the possibility of using infrared reflections as a navigational method and how to achieve distinct reflection measurements from a surface. The thesis also discusses the possibility of using several units on a larger scale. In the progress of the project, a prototype vehicle was built to conduct the experiments to identify the suitability of infrared navigation. The testing of the prototype shows that navigation by IR can be very reliable under controlled circumstances. The project also explored how hierarchical software architecture stands in comparison to purely local or centralized software architecture.
I världen växer forskning på självgående fordon dagligen. Målet med detta projekt var att skapa ett självgående fordon och utforska möjligheterna att använda infraröda reflektioner som navigeringsmetod och hur man kan uppnå distinkta mätvärden. Avhandlingen diskuterar även möjligheterna att använda flera prototyper i en större skala. Under projektets gång byggdes ett prototypfordon för att genomföra experimenten angående lämpligheten med navigering via infrarött ljus. Tester med prototypen visar att navigering via infrarött ljus är väldigt pålitligt under kontrollerade omständigheter. Projektet utforskar även hur hierarkisk mjukvaruarkitektur står sig mot helt lokal eller centraliserad mjukvaruarkitektur.

In algorithmic computing, the program follows a predefined set of rules – the algorithm. The analyst/designer of the program analyzes the intended tasks of the program, defines the rules for its expected behaviour and programs the implementation. The creators of algorithmic software must therefore foresee, identify and implement all possible cases for its behaviour in the future application! However, what if the problem is not fully defined? Or the environment is uncertain? What if situations are too complex to be predicted? Or the environment is changing dynamically? In many such cases algorithmic computing fails. In such situations, the software needs an additional degree of freedom: Autonomy! Autonomy allows software to adapt to partially defined problems, to uncertain or dynamically changing environments and to situations that are too complex to be predicted. As more and more applications – such as autonomous cars and planes, adaptive power grid management, survivable networks, and many more – fall into this category, a gradual switch from algorithmic computing to autonomic computing takes place. Autonomic computing has become an important software engineering discipline with a rich literature, an active research community, and a growing number of applications.:Introduction 5 1 A Process Data Based Autonomic Optimization of Energy Efficiency in Manufacturing Processes, Daniel Höschele 9 2 Eine autonome Optimierung der Stabilität von Produktionsprozessen auf Basis von Prozessdaten, Richard Horn 25 3 Assuring Safety in Autonomous Systems, Christian Rose 41 4 MAPE-K in der Praxis - Grundlage für eine mögliche automatische Ressourcenzuweisung, in der Cloud Michael Schneider 59

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Não recebi financiamento
Autonomous mobile robots are a special category of robots designed for performing tasks without the intervention of human beings. Some robots are designed to perform tasks in completely inhospitable environments such as the earth´s subsurface, the ocean depths or spatial exploration. In order to consider a robot as autonomous, a fundamental premise is to have self-adaptation capabilities. Over the last years, the advances in technology allow the development of self-adaptive systems, which are able to manage themselves to recuperate from faults or even change their behavior and structure in order to improve the quality of the delivered service. A critical point when building any software is its architecture, i.e., its structural organization in a set of interacting components. In this context, reference architecture is a technique that is well known for combining the best practices, patterns and strategies for building and standardizing domain specific software. Nowadays, there is a lack of studies presenting reference architectures for structuring self-adaptive software of mobile robots in order to decrease maintenance efforts. A number of studies claim that self-adaptive systems are based on the control theory and, more specifically, on the use of control loops in their architecture to perform adaptations. Therefore, this master thesis proposes SARAMR, a control loop-based reference architecture whose goal is to make maintenance activities a more productive task. The employment of the architecture divides the whole system in two modules; base application and adaptation module. The adaptation module encompasses the control loops and the base application is further divided into three other components: environment, behaviors and the electromechanical part. SARAMR was qualitatively evaluated by means of the development of two applications: a self-adaptive wall follower mobile robot and another conventional one to performing monitoring in in-door environments. Next, some maintenance activities were created to investigate the effort of applying them. We have observed that the separation of concerns of our architecture allows new components to be added causing less impacts than in systems developed in an adhoc way.
Robôs móveis autônomos fazem parte de uma categoria especial de robôs projetados para realizar tarefas sem a intervenção de seres humanos. Alguns robôs são projetados para realizar tarefas em ambientes completamente inóspitos à vida humana como no subsolo terrestre, nas profundezas de oceanos ou na exploração espacial. Para que um robô seja considerado autônomo, uma premissa fundamental é possuir capacidades de autoadaptação. Nos últimos anos, os avanços da tecnologia possibilitaram o desenvolvimento de sistemas robóticos autoadaptativos, que são capazes de gerenciarem a si próprios, se recuperarem de falhas e também de alterarem seu comportamento e estrutura com o objetivo de otimizar e/ou manter a qualidade do serviço (QoS) oferecido. Uma questão crítica para a concepção e construção de qualquer sistema de software é sua arquitetura, isto é, sua organização estrutural em um conjunto de componentes que interagem. Nesse contexto, a utilização de arquiteturas de referência é uma abordagem conhecida atualmente por combinar as melhores práticas, padrões e estratégias para a construção e padronização de sistemas de software para um determinado domínio. Atualmente, nota-se uma carência de estudos que apresentem arquiteturas de referência para estruturar o software de robôs móveis autoadaptativos de forma a facilitar atividades de manutenção nesses sistemas. Muitos estudos apontam que sistemas autoadaptativos são baseados na teoria do controle e mais especificamente na utilização de loops de controle em sua arquitetura para realizar as adaptações. Diante disso, este trabalho propõe a arquitetura de referência SARAMR, uma arquitetura de referência baseada em loops de controle cujo objetivo é facilitar atividades de manutenção no software desses sistemas. A utilização da arquitetura divide o sistema em dois módulos: aplicação base e módulo de adaptação. O módulo de adaptação envolve os loops de controle e a aplicação base ainda é subdividida em três componentes: ambiente, comportamentos e a parte eletromecânica. SARAMR foi avaliada de forma qualitativa mediante o desenvolvimento duas aplicações: um robô autoadaptativo seguidor de paredes e um outro convencional de patrulhamento. Depois disso, algumas manutenções evolutivas foram idealizadas no sentido de averiguar o esforço de aplicá-las. Constatou-se que a separação de interesses existente na arquitetura permite que novos componentes possam ser adicionados com impacto menor do que em sistemas que não usam essa arquitetura.

Orientador : Eleri Cardozo
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação
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Resumo: Pinto, Rossano Pablo, "Sessão de Acesso TINA com Suporte à Adaptação de Serviços Através de Agentes Móveis". Tese de Mestrado - DCA/FEEC/UNICAMP, Campinas, SP. Julho 2001. Esta dissertação apresenta a implementação de uma protótipo que faz uso da Arquitetura de Serviço TINA e de um modelo para adaptação de serviços em domínios visitados (MASDV) visando prover ubiqüidade de serviços. TINA apresenta conceitos importantes para a área de telecomunicações como a separação do acesso e uso de serviços. Estas separações são chamadas de sessões. A arquitetura de serviço define três sessões: acesso, serviço e comunicação. MASDV supri algumas deficiências encontradas em TINA e faz uso de agentes móveis "inteligentes" (autônomos) na adaptação de serviços para uso em domínios que um usuário não possui contrato
Abstract: This dissertation presents the implementation of a prototype that is based upon the TINA ServiceArchitecture and upon a model for service adaptation under visited domains (SAVD) in order to provide service ubiquity. TINA offers important concepts to the telecommunications area, like separation between the access and use of services. These separations are called sessionso The service architecture defines three sessions: access, service and communication. SAVD completes TINA where some desireble features lacko SAVD uses Intelligent (Autonomous) Mobile Agents to adapt services for use in domains which a user hasn't signed a contract
Mestrado
Engenharia de Computação
Mestre em Engenharia Elétrica

Self-adaptive systems have limited time to adjust their configurations whenever their adaptation goals, i.e., quality requirements, are violated due to some runtime uncertainties. Within the available time, they need to analyze their adaptation space, i.e., a set of configurations, to find the best adaptation option, i.e., configuration, that can achieve their adaptation goals. Existing formal analysis approaches find the best adaptation option by analyzing the entire adaptation space. However, exhaustive analysis requires time and resources and is therefore only efficient when the adaptation space is small. The size of the adaptation space is often in hundreds or thousands, which makes formal analysis approaches inefficient in large-scale self-adaptive systems. In this thesis, we tackle this problem by presenting an online learning approach that enables formal analysis approaches to analyze large adaptation spaces efficiently. The approach integrates with the standard feedback loop and reduces the adaptation space to a subset of adaptation options that are relevant to the current runtime uncertainties. The subset is then analyzed by the formal analysis approaches, which allows them to complete the analysis faster and efficiently within the available time. We evaluate our approach on two different instances of an Internet of Things application. The evaluation shows that our approach dramatically reduces the adaptation space and analysis time without compromising the adaptation goals.

Presently, most spacecraft are controlled from ground involving activities such as up-linking the schedule of daily operations and monitoring health parameters. These activities lead to a cognitive overload on human operators. Imaging/science opportunities are lost, if any discrepancies occur during the execution of pre-planned sequences. Consequently, advanced space exploration systems for future needs demand on-board intelligence and autonomy. This thesis attempts to solve the problem of providing an adequate degree of autonomy in future generation of spacecraft. The autonomous spacecraft accept high-level goals from users and make decisions on-board to generate detailed command schedules satisfying stringent constraints posed by the harsh environment of the space, visibility criteria and scarce on-board resources. They reconfigure themselves in case of any failure and re-plan when needed. Autonomy concepts are derived in the context of complex systems by drawing analogy to living organisms and social organisations. A general autonomy framework may be defined with a six level structure comprising of the following capabilities -reflexes, awareness, self-regulation, self-healing, self-adaptation and self-evolution. A generic and reusable software architecture is proposed using hybrid multi-agent systems, which are arranged in a hierarchical manner using two types of decomposition viz. stratum and layer. The software architecture of the autonomous spacecraft is modeled as a stratified agent with a deliberative stratum, which achieves adaptive behaviour and a reactive stratum, which achieves reactive behaviour. Each individual agent has a generic structure comprising of perception, action, communication and knowledge components. It achieves the specialist capability through model-based reasoning. The knowledge models encompass: Planning knowledge describing higher-level goals, task structure and method of achieving the goals, Control knowledge encompassing the static and dynamic models of the spacecraft and Diagnostic knowledge incorporating the cause-effect relationships. The deliberative stratum is capable of planning in different time horizons and is, in turn, organised into a hierarchical agent system with three layers corresponding to different time horizons. It is composed of a long-term, medium-term and short-term planning agents, focusing on strategic issues, spacecraft level resources and specific spacecraft states respectively. The power of Petri nets is exploited for knowledge modeling as well as for plan representation. The ability of Petri nets to represent causality, concurrency and conflict relations explicitly makes it an excellent tool for representing the planning problem. Hierarchical Timed Petri Net is chosen for our modeling, since it captures the temporal requirements of the real-time spacecraft operations as well as facilitates the modeling of the system with multiple levels of abstraction. The necessary primitives for the plan representation are defined. In hierarchical modeling using Petri nets, refinement is done by a compound (high-level) transition. A compound transition models either a complex activity, which corresponds to high-level operation on spacecraft or a method, which corresponds to the agent capability. At the lowest layer, a transition in the plan represents a primitive command to the spacecraft, such as ‘switch on camera’. The Petri net unfolding technique, which is a partial order approach, is applied to derive the plans from the dynamic knowledge models. This tackles the problem of combinatorial explosion. A hierarchical planning approach is followed, in which the abstract plan is recursively decomposed using the unfolding technique and refined by way of exercising the appropriate decisions in each layer. The reactive stratum is configured with three peer level agents. The control agent executes the command schedule and has the capability for reflex action. Structural properties of Petri nets are exploited by the execution-monitoring agent and the diagnostic agent for system level diagnosis. Fault tree method is applied for fine granularity diagnosis. The resultant architecture is a cost-effective solution, since it permits reusability of knowledge models across similar missions. The knowledge models are formally verified for ensuring the absence of deadlocks, buffer overflows, recoverability and detection of unreachable modules using Petri net properties such as reachability, liveness, boundedness, safeness, reversibility and home state. The high-risk components are subjected to safety property verification, which makes the system rugged. The hierarchical composition of Petri net models (which are independently verified), preserves liveness and boundedness characteristics and thus ensuring the reliability of the integrated models. This, in turn, ensures that reliable plans are generated on-board using these good quality models. The models of the system components viz. partial order plan, conditional plan, dynamic world model, reflex model, resource model and the hierarchical models are developed and demonstrated using HPSIM and Moses Tool Suite, using examples from spacecraft domain. The long-term planning agent, with hierarchical world models, for handling high-level goals is developed and simulated using Moses Tool Suite. The plan generation using unfolding approach is demonstrated using VIPTool, which has the partial order analysis capability. In summary, the main contributions include (a) Definition of a general framework for spacecraft autonomy; (b) design of a generic and reusable architecture for autonomous spacecraft using hybrid multi-agent concepts; (c) unified knowledge representation and reasoning using Petri nets across various strata/layers; (d) application of Petri net unfolding technique in a hierarchical manner for plan generation; (e) use of structural properties of Petri nets for fault identification and location; (f) verification and validation of Petri net models using Petri net properties and (g) simulation and demonstration of the system components viz. partial order plan, conditional plan, dynamic world model, reflex model, resource model and hierarchical models, by developing examples from spacecraft domain, using HPSIM and Moses Tool Suite and demonstration of plan generation using unfolding technique using VIPTool.

Presently, most spacecraft are controlled from ground involving activities such as up-linking the schedule of daily operations and monitoring health parameters. These activities lead to a cognitive overload on human operators. Imaging/science opportunities are lost, if any discrepancies occur during the execution of pre-planned sequences. Consequently, advanced space exploration systems for future needs demand on-board intelligence and autonomy. This thesis attempts to solve the problem of providing an adequate degree of autonomy in future generation of spacecraft. The autonomous spacecraft accept high-level goals from users and make decisions on-board to generate detailed command schedules satisfying stringent constraints posed by the harsh environment of the space, visibility criteria and scarce on-board resources. They reconfigure themselves in case of any failure and re-plan when needed. Autonomy concepts are derived in the context of complex systems by drawing analogy to living organisms and social organisations. A general autonomy framework may be defined with a six level structure comprising of the following capabilities -reflexes, awareness, self-regulation, self-healing, self-adaptation and self-evolution. A generic and reusable software architecture is proposed using hybrid multi-agent systems, which are arranged in a hierarchical manner using two types of decomposition viz. stratum and layer. The software architecture of the autonomous spacecraft is modeled as a stratified agent with a deliberative stratum, which achieves adaptive behaviour and a reactive stratum, which achieves reactive behaviour. Each individual agent has a generic structure comprising of perception, action, communication and knowledge components. It achieves the specialist capability through model-based reasoning. The knowledge models encompass: Planning knowledge describing higher-level goals, task structure and method of achieving the goals, Control knowledge encompassing the static and dynamic models of the spacecraft and Diagnostic knowledge incorporating the cause-effect relationships. The deliberative stratum is capable of planning in different time horizons and is, in turn, organised into a hierarchical agent system with three layers corresponding to different time horizons. It is composed of a long-term, medium-term and short-term planning agents, focusing on strategic issues, spacecraft level resources and specific spacecraft states respectively. The power of Petri nets is exploited for knowledge modeling as well as for plan representation. The ability of Petri nets to represent causality, concurrency and conflict relations explicitly makes it an excellent tool for representing the planning problem. Hierarchical Timed Petri Net is chosen for our modeling, since it captures the temporal requirements of the real-time spacecraft operations as well as facilitates the modeling of the system with multiple levels of abstraction. The necessary primitives for the plan representation are defined. In hierarchical modeling using Petri nets, refinement is done by a compound (high-level) transition. A compound transition models either a complex activity, which corresponds to high-level operation on spacecraft or a method, which corresponds to the agent capability. At the lowest layer, a transition in the plan represents a primitive command to the spacecraft, such as ‘switch on camera’. The Petri net unfolding technique, which is a partial order approach, is applied to derive the plans from the dynamic knowledge models. This tackles the problem of combinatorial explosion. A hierarchical planning approach is followed, in which the abstract plan is recursively decomposed using the unfolding technique and refined by way of exercising the appropriate decisions in each layer. The reactive stratum is configured with three peer level agents. The control agent executes the command schedule and has the capability for reflex action. Structural properties of Petri nets are exploited by the execution-monitoring agent and the diagnostic agent for system level diagnosis. Fault tree method is applied for fine granularity diagnosis. The resultant architecture is a cost-effective solution, since it permits reusability of knowledge models across similar missions. The knowledge models are formally verified for ensuring the absence of deadlocks, buffer overflows, recoverability and detection of unreachable modules using Petri net properties such as reachability, liveness, boundedness, safeness, reversibility and home state. The high-risk components are subjected to safety property verification, which makes the system rugged. The hierarchical composition of Petri net models (which are independently verified), preserves liveness and boundedness characteristics and thus ensuring the reliability of the integrated models. This, in turn, ensures that reliable plans are generated on-board using these good quality models. The models of the system components viz. partial order plan, conditional plan, dynamic world model, reflex model, resource model and the hierarchical models are developed and demonstrated using HPSIM and Moses Tool Suite, using examples from spacecraft domain. The long-term planning agent, with hierarchical world models, for handling high-level goals is developed and simulated using Moses Tool Suite. The plan generation using unfolding approach is demonstrated using VIPTool, which has the partial order analysis capability. In summary, the main contributions include (a) Definition of a general framework for spacecraft autonomy; (b) design of a generic and reusable architecture for autonomous spacecraft using hybrid multi-agent concepts; (c) unified knowledge representation and reasoning using Petri nets across various strata/layers; (d) application of Petri net unfolding technique in a hierarchical manner for plan generation; (e) use of structural properties of Petri nets for fault identification and location; (f) verification and validation of Petri net models using Petri net properties and (g) simulation and demonstration of the system components viz. partial order plan, conditional plan, dynamic world model, reflex model, resource model and hierarchical models, by developing examples from spacecraft domain, using HPSIM and Moses Tool Suite and demonstration of plan generation using unfolding technique using VIPTool.

This thesis presents a comparison of controller designs and a system software design for a general Guidance, Navigation and Control (GNC) system. The first part of the thesis investigates four control algorithms based on Lyapunov Direct Method in conjunction with sliding mode and adaptive control. These algorithms address three practical issues in controller design: maximum actuation limitation, external disturbances, and imperfect dynamic models. Each of the algorithms is proven to be globally asymptotically stable within its constraints. A simulation is then used to model a cube-satellite attitude maneuver using each of the controllers to evaluate its performance. The second part of this thesis discusses the development of a high-level flight software architecture capable of handling common tasks, including ground station communication and attitude maneuvers, as well as power or device failures.
text

The subject of the thesis is the design and implementation of a modular control system environment, which could be used in robotics. Both autonomous and guided robots are supported. The higher-level software com- ponents like localization, steering, decision making, etc. are effectively sepa- rated from the underlying hardware devices and their communication protocols in the environment. Based on the layered design, hardware-independent algo- rithms can be implemented. These can run on different hardware platforms just by exchanging specific device drivers. Written in C++ using standard libraries, the final software is highly portable and extensible. Support for new platforms and hardware modules can be implemented easily. The whole sys- tem was tested on two robots and the particular instances of the systems built using this development environment are included in the solution and partially described in the thesis.

In algorithmic computing, the program follows a predefined set of rules – the algorithm. The analyst/designer of the program analyzes the intended tasks of the program, defines the rules for its expected behaviour and programs the implementation. The creators of algorithmic software must therefore foresee, identify and implement all possible cases for its behaviour in the future application! However, what if the problem is not fully defined? Or the environment is uncertain? What if situations are too complex to be predicted? Or the environment is changing dynamically? In many such cases algorithmic computing fails. In such situations, the software needs an additional degree of freedom: Autonomy! Autonomy allows software to adapt to partially defined problems, to uncertain or dynamically changing environments and to situations that are too complex to be predicted. As more and more applications – such as autonomous cars and planes, adaptive power grid management, survivable networks, and many more – fall into this category, a gradual switch from algorithmic computing to autonomic computing takes place. Autonomic computing has become an important software engineering discipline with a rich literature, an active research community, and a growing number of applications.