Nanosat Intelligent Power System Development

NASA Goddard Space Flight Center is developing a class of satellites called nano-satellites. The technologies developed for these satellites will enable a class of constellation missions for the NASA Space Science Sun-Earth Connections theme and will be of great benefit to other NASA enterprises. A major challenge for these missions is meeting significant scientific- objectives with limited onboard and ground-based resources. Total spacecraft power is limited by the small satellite size. Additionally, it is highly desirable to minimize operational costs by limiting the ground support required to manage the constellation. This paper will describe how these challenges are met in the design of the nanosat power system. We will address the factors considered and tradeoffs made in deriving the nanosat power system architecture. We will discuss how incorporating onboard fault detection and correction capability yields a robust spacecraft power bus without the mass and volume penalties incurred from redundant systems and describe how power system efficiency is maximized throughout the mission duration

Fault Tolerance for Spacecraft Attitude Management

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/83657/1/AIAA-2010-8301-426.pd

RIACS

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities that serves as a bridge between NASA and the academic community. Under a five-year co-operative agreement with NASA, research at RIACS is focused on areas that are strategically enabling to the Ames Research Center's role as NASA's Center of Excellence for Information Technology. The primary mission of RIACS is charted to carry out research and development in computer science. This work is devoted in the main to tasks that are strategically enabling with respect to NASA's bold mission in space exploration and aeronautics. There are three foci for this work: (1) Automated Reasoning. (2) Human-Centered Computing. and (3) High Performance Computing and Networking. RIACS has the additional goal of broadening the base of researcher in these areas of importance to the nation's space and aeronautics enterprises. Through its visiting scientist program, RIACS facilitates the participation of university-based researchers, including both faculty and students, in the research activities of NASA and RIACS. RIACS researchers work in close collaboration with NASA computer scientists on projects such as the Remote Agent Experiment on Deep Space One mission, and Super-Resolution Surface Modeling

A Hybrid Procedural/Deductive Executive For Autonomous Spacecraft

The New Millennium Remote Agent (NMRA) will be the first AI system to control an actual spacecraft. The spacecraft domain places a strong premium on autonomy and requires dynamic recoveries and robust concurrent execution, all in the presence of tight real-time deadlines, changing goals, scarce resource constraints, and a wide variety of possible failures. To achieve this level of execution robustness, we have integrated a procedural executive based on generic procedures with a deductive model-based executive. A procedural executive provides sophisticated control constructs such as loops, parallel activity, locks, and synchronization which are used for robust schedule execution, hierarchical task decomposition, and routine configuration management. A deductive executive provides algorithms for sophisticated state inference and optimal failure recovery planning. The integrated executive enables designers to code knowledge via a combination of procedures and declarative models, yielding ..

A hybrid procedural/deductive executive for autonomous spacecraft

The New Millennium Remote Agent (NMRA) will be the rst AI system to control an actual spacecraft. The spacecraft domain places a strong premium on autonomy and requires dynamic recoveries and robust concurrent execution, all in the presence of tight real-time deadlines, changing goals, scarce resource constraints, and a wide variety of possible failures. To achieve this level of execution robustness, we have integrated a procedural executive based on generic procedures with a deductive model-based reasoning system. The resulting system enables designers to code knowledge via a combination of procedures and declarative models, yielding a rich modeling capability suitable to the challenges of real spacecraft control.

Timed model-based programming : executable specifications for robust mission-critical sequences

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2003.Includes bibliographical references (p. 195-204).There is growing demand for high-reliability embedded systems that operate robustly and autonomously in the presence of tight real-time constraints. For robotic spacecraft, robust plan execution is essential during time-critical mission sequences, due to the very short time available for recovery from anomalies. Traditional approaches to encoding these sequences can lead to brittle behavior under off-nominal execution conditions, due to the high level of complexity in the control specification required to manage the complex spacecraft system interactions. This work describes timed model-based programming, a novel approach for encoding and robustly executing mission-critical spacecraft sequences. The timed model-based programming approach addresses the issues of sequence complexity and unanticipated low-level system interactions by allowing control programs to directly read or write "hidden" states of the plant, that is, states that are not directly observable or controllable. It is then the responsibility of the program's execution kernel to map between hidden states and the plant sensors and control variables. This mapping is performed automatically by a deductive controller using a common-sense plant model, freeing the programmer from the error-prone process of reasoning through a complex set of interactions under a range of possible failure situations. Time is central to the execution of mission-critical sequences; a robust executive must consider time in its control and behavior models, in addition to reactively managing complexity.(cont.) In timed model-based programming, control programs express goals and constraints in terms of both system state and time. Plant models capture the underlying behavior of the system components, including nominal and off-nominal modes, probabilistic transitions, and timed effects such as state transition latency. The contributions of this work are threefold. First, a semantic specification of the timed model-based programming approach is provided. The execution semantics of a timed model-based program are defined in terms of legal state evolutions of a physical plant, represented as a factored Partially Observable Semi-Markov Decision Process. The second contribution is the definition of graphical and textual languages for encoding timed control programs and plant models. The adoption of a visual programming paradigm allows timed model-based programs to be specified and readily inspected by the systems engineers in charge of designing the mission-critical sequences. The third contribution is the development of a Timed Model-based Executive, which takes as input a timed control program and executes it, using timed plant models to track states, diagnose faults and generate control actions. The Timed Model-based Executive has been implemented and demonstrated on a representative spacecraft scenario for Mars entry, descent and landing.by Michel Donald Ingham.Sc.D

Intelligent interface agents for biometric applications

This thesis investigates the benefits of applying the intelligent agent paradigm to biometric identity verification systems. Multimodal biometric systems, despite their additional complexity, hold the promise of providing a higher degree of accuracy and robustness. Multimodal biometric systems are examined in this work leading to the design and implementation of a novel distributed multi-modal identity verification system based on an intelligent agent framework. User interface design issues are also important in the domain of biometric systems and present an exceptional opportunity for employing adaptive interface agents. Through the use of such interface agents, system performance may be improved, leading to an increase in recognition rates over a non-adaptive system while producing a more robust and agreeable user experience. The investigation of such adaptive systems has been a focus of the work reported in this thesis. The research presented in this thesis is divided into two main parts. Firstly, the design, development and testing of a novel distributed multi-modal authentication system employing intelligent agents is presented. The second part details design and implementation of an adaptive interface layer based on interface agent technology and demonstrates its integration with a commercial fingerprint recognition system. The performance of these systems is then evaluated using databases of biometric samples gathered during the research. The results obtained from the experimental evaluation of the multi-modal system demonstrated a clear improvement in the accuracy of the system compared to a unimodal biometric approach. The adoption of the intelligent agent architecture at the interface level resulted in a system where false reject rates were reduced when compared to a system that did not employ an intelligent interface. The results obtained from both systems clearly express the benefits of combining an intelligent agent framework with a biometric system to provide a more robust and flexible application