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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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We developed a framework that looks at both cost and risk early in the design process in order to determine the investment strategy in new technology development that will lead to the lowest risk mission possible which enables desired science return within a given budget.
The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattem recognition to radically increase science retum by enabling intelligent downlink selection and autonomous retargeting. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.
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Practitioners of artificial intelligence are being engaged to help develop the next generation of flight software for NASA missions, in partnership with other computer scientists, mission designers, operations personnel, spacecraft engineers, systems engineers, software engineers, and scientists.
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We provide a useful set of metrics and present an example application of the method to assess merit of hypothetical future Mars rover performance relative to the MER baseline.
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We describe the current mission operations flow for the Earth Observing-1 spacecraft as well as the more autonomous operations to which we are transitioning as part of the Autonomous Sciencecrat Experiment (ASE).