Engineering topics
Publications and source records attributed to Doyle, R..
The Autonomous Sciencecraft Experiment flight demonstration (ASE) will fly onboard the US Air Forces's TechSat-21 constellation, an unclassified mission scheduled for launch in 2004. ASE will use onboard science analysis, replanning, robust execution, and formation flying to radically increase science return by enabling intelligent downlink selection and autonomous retargeting.
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The 2nd GSFC-JPL QMSW workshop brought together 56 participants mostly from GSFC and JPL to focus on critical challenges for mission software.
The Mission And Computing Support (MACS) Contractor in accordance with contract number 958226 shall provide engineering, operations, and maintenance support to JPL core systems and Flight Projects.
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NASA's Deep Space One (DS1) mission is unprecedented.
The early twenty-first century will witness a new era of space exploration characterized by sustained in-depth scientific studies at increasingly remote environments with themes as compelling as the search for life in the universe.
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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It is our aim by launching a series of workshops on the topic of highly autonomous systems to reach out to the larger community interested in technology development for remotely deployed systems, particularly those for exploration.
Any attempt to introduce automation into the monitoring of complex physical systems must start from a robust anomaly detection capability. This task is far from straightforward, for a single definition of what constitutes an anomaly is difficult to come by. In addition, to make the monitoring process efficient, and to avoid the potential for information overload on human operators, attention focusing must also be addressed. When an anomaly occurs, more often than not several sensors are affected, and the partially redundant information they provide can be confusing, particularly in a crisis situation where a response is needed quickly.
Any attempt to introduce automation into the monitoring of complex physical systems must start from a robust anomaly detection capability. This task is far from straightforward, for a single definition of what constitutes an anomaly is difficult to come by. In addition, to make the monitoring process efficient, and to avoid the potential for information overload on human operators, attention focusing must also be addressed. When an anomaly occurs, more often than not several sensors are affected, and the partially redundant information they provide can be confusing, particularly in a crisis situation where a response is needed quickly. Previous results on extending traditional anomaly detection techniques are summarized. The focus of this paper is a new technique for attention focusing.