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  • 1
    ISSN: 1573-7527
    Keywords: autonomous robots ; agent architectures ; action selection and planning ; diagnosis ; integration and coordination of multiple activities ; fault protection ; operations ; real-time systems ; modeling
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract This paper describes the New Millennium Remote Agent (NMRA) architecture for autonomous spacecraft control systems. The architecture supports challenging requirements of the autonomous spacecraft domain not usually addressed in mobile robot architectures, including highly reliable autonomous operations over extended time periods in the presence of tight resource constraints, hard deadlines, limited observability, and concurrent activity. A hybrid architecture, NMRA integrates traditional real-time monitoring and control with heterogeneous components for constraint-based planning and scheduling, robust multi-threaded execution, and model-based diagnosis and reconfiguration. Novel features of this integrated architecture include support for robust closed-loop generation and execution of concurrent temporal plans and a hybrid procedural/deductive executive. We implemented a prototype autonomous spacecraft agent within the architecture and successfully demonstrated the prototype in the context of a challenging autonomous mission scenario on a simulated spacecraft. As a result of this success, the integrated architecture has been selected to fly as an autonomy experiment on Deep Space One (DS-1), the first flight of NASA';s New Millennium Program (NMP), which will launch in 1998. It will be the first AI system to autonomously control an actual spacecraft.
    Type of Medium: Electronic Resource
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  • 2
    Publication Date: 2011-08-19
    Description: The problem addressed is that of obtaining reduced-order component models for use in simulating the dynamics of a multibody system. In certain cases, nonlinear system models may be constructed using linear dynamic models for each component, but allowing large angle motion between components. Without some form of model reduction, system models constructed in this manner may be too large for use in control system design and simulation trades. This paper analyzes one method of component model reduction that allows systems level requirements (e.g., capturing the effect of body 1 reaction wheel noise on body 2 camera pointing) to aid in the selection of the reduced-order component models. Briefly stated, important modes are selected at the system level and projected onto the components, and reduced-order components are then assembled into a reduced-order system model that retains the projected modes.
    Keywords: STRUCTURAL MECHANICS
    Type: Journal of Guidance, Control, and Dynamics (ISSN 0731-5090); 13; 905-912
    Format: text
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  • 3
    Publication Date: 2013-08-31
    Description: The problem of acquiring a simple but sufficiently accurate model of a dynamic system is made more difficult when the dynamic system of interest is a multibody system comprised of several components. A low order system model may be created by reducing the order of the component models and making use of various available multibody dynamics programs to assemble them into a system model. The difficulty is in choosing the reduced order component models to meet system level requirements. The projection and assembly method, proposed originally by Eke, solves this difficulty by forming the full order system model, performing model reduction at the the system level using system level requirements, and then projecting the desired modes onto the components for component level model reduction. The projection and assembly method is analyzed to show the conditions under which the desired modes are captured exactly; to the numerical precision of the algorithm.
    Keywords: COMPUTER PROGRAMMING AND SOFTWARE
    Type: Proceedings of the 3rd Annual Conference on Aerospace Computational Control, Volume 2; p 778-791
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  • 4
    Publication Date: 2019-07-18
    Description: This paper describes the integration of the Remote Agent (RA), a spacecraft autonomy system which is scheduled to control the Deep Space 1 spacecraft during a flight experiment in 1999. The RA is a reusable, model-based autonomy system that is quite different from software typically used to control an aerospace system. We describe the integration challenges we faced, how we addressed them, and the lessons learned. We focus on those aspects of integrating the RA that were either easier or more difficult than integrating a more traditional large software application because the RA is a model-based autonomous system. A number of characteristics of the RA made integration process easier. One example is the model-based nature of RA. Since the RA is model-based, most of its behavior is not hard coded into procedural program code. Instead, engineers specify high level models of the spacecraft's components from which the Remote Agent automatically derives correct system-wide behavior on the fly. This high level, modular, and declarative software description allowed some interfaces between RA components and between RA and the flight software to be automatically generated and tested for completeness against the Remote Agent's models. In addition, the Remote Agent's model-based diagnosis system automatically diagnoses when the RA models are not consistent with the behavior of the spacecraft. In flight, this feature is used to diagnose failures in the spacecraft hardware. During integration, it proved valuable in finding problems in the spacecraft simulator or flight software. In addition, when modifications are made to the spacecraft hardware or flight software, the RA models are easily changed because they only capture a description of the spacecraft. one does not have to maintain procedural code that implements the correct behavior for every expected situation. On the other hand, several features of the RA made it more difficult to integrate than typical flight software. For example, the definition of correct behavior is more difficult to specify for a system that is expected to reason about and flexibly react to its environment than for a traditional flight software system. Consequently, whenever a change is made to the RA it is more time consuming to determine if the resulting behavior is correct. We conclude the paper with a discussion of future work on the Remote Agent as well as recommendations to ease integration of similar autonomy projects.
    Keywords: Cybernetics, Artificial Intelligence and Robotics
    Format: text
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  • 5
    Publication Date: 2018-06-08
    Description: This paper describes the New Millennium Remote Agent (NMRA) architecture for autonomous spacecraft control systems. This architecture integrates traditional real-time monitoring and control with constraint-based planning and scheduling, robust multi-threaded execution, and model-based diagnosis and reconfiguration.
    Format: text
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  • 6
    Publication Date: 2019-01-25
    Description: The Cassini Attitude and Articulation Control Subsystem (AACS) is responsible for determining and controlling the spacecraft attitude including instrument pointing, antenna pointing, and thrust vector pointing during velocity change maneuvers. The 12 year mission life, long round-trip light time, and extended periods of coast without continuous ground control drive the AACS flight software design in the directions of autonomy, fault tolerance, and modularity to accommodate planned upgrades in flight. The Cassini AACS Flight Software is depicted in increasing levels of detail using a Context Diagram, Architecture Diagrams (i.e., Dependency Diagrams), an Object Diagram for each object, and a Statechart (i.e., State Transition Diagram) for each object. The detail contained in the diagrams is enhanced and refined during the Requirements and Design Phases of both Subsystem and Software Development. Examples of all the diagrams as well as the criteria for object selection, the advantages of statecharts, and the ease of modifying the design to accommodate changes in scope are described.
    Keywords: COMPUTER PROGRAMMING AND SOFTWARE
    Type: (ISSN 0065-3438); sic Space Science; U
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  • 7
    Publication Date: 2019-07-13
    Description: NASA's Juno mission launched in 2011 and will explore the Jupiter system starting in 2016. Juno's suite of instruments is designed to investigate the atmosphere, gravitational fields, magnetic fields, and auroral regions. Its low perijove polar orbit will allow it to explore portions of the Jovian environment never before visited. While the Juno mission is not orbiting or flying close to Europa or the other Galilean satellites, planetary protection requirements for avoiding the contamination of Europa have been taken into account in the Juno mission design.The science mission is designed to conclude with a deorbit burn that disposes of the spacecraft in Jupiter's atmosphere. Compliance with planetary protection requirements is verified through a set of analyses including analysis of initial bioburden, analysis of the effect of bioburden reduction due to the space and Jovian radiation environments, probabilistic risk assessment of successful deorbit, Monte-Carlo orbit propagation, and bioburden reduction in the event of impact with an icy body.
    Keywords: Lunar and Planetary Science and Exploration
    Type: COSPAR Scientific Assembly; Jul 18, 2010 - Jul 25, 2010; Bremen; Germany
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  • 8
    Publication Date: 2019-07-13
    Description: The Remote Agent (RA) is an Artificial Intelligence (AI) system which automates some of the tasks normally reserved for human mission operators and performs these tasks autonomously on-board the spacecraft. These tasks include activity generation, sequencing, spacecraft analysis, and failure recovery. The RA will be demonstrated as a flight experiment on Deep Space One (DSI), the first deep space mission of the NASA's New Millennium Program (NMP). As we moved from prototyping into actual flight code development and teamed with ground operators, we made several major extensions to the RA architecture to address the broader operational context in which PA would be used. These extensions support ground operators and the RA sharing a long-range mission profile with facilities for asynchronous ground updates; support ground operators monitoring and commanding the spacecraft at multiple levels of detail simultaneously; and enable ground operators to provide additional knowledge to the RA, such as parameter updates, model updates, and diagnostic information, without interfering with the activities of the RA or leaving the system in an inconsistent state. The resulting architecture supports incremental autonomy, in which a basic agent can be delivered early and then used in an increasingly autonomous manner over the lifetime of the mission. It also supports variable autonomy, as it enables ground operators to benefit from autonomy when L'@ey want it, but does not inhibit them from obtaining a detailed understanding and exercising tighter control when necessary. These issues are critical to the successful development and operation of autonomous spacecraft.
    Keywords: Cybernetics
    Type: RIACS-TR-98.08 , Autonomous Agents; Jan 01, 1998
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  • 9
    Publication Date: 2019-07-13
    Description: Conference topics included definition of tool requirements, advanced multibody component representation descriptions, model reduction, parallel computation, real time simulation, control design and analysis software, user interface issues, testing and verification, and applications to spacecraft, robotics, and aircraft.
    Keywords: COMPUTER PROGRAMMING AND SOFTWARE
    Type: NASA-CR-186446 , JPL-PUBL-89-45-VOL-1 , NAS 1.26:186446 , Nov 01, 1989; Oxnard, CA; United States
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  • 10
    Publication Date: 2019-07-13
    Description: This volume of the conference proceedings contain papers and discussions in the following topical areas: Parallel processing; Emerging integrated capabilities; Low order controllers; Real time simulation; Multibody component representation; User environment; and Distributed parameter techniques.
    Keywords: COMPUTER PROGRAMMING AND SOFTWARE
    Type: NASA-CR-186447 , JPL-PUBL-89-45-VOL-2 , NAS 1.26:186447 , Nov 01, 1989; Oxnard, CA; United States
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