From Mission Objectives to Design: An Efficient Framework for Downselection in Robotic Space Exploration
Author(s)
Lafleur, Jarret M.
Sharma, Jonathan L.
Apa, Jillian
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Abstract
One of the most critical tasks in any design process is the initial conversion of mission or
program objectives into a baseline system architecture. Approaches to this task commonly
rely on qualitative assessments of design options and detailed sizing of a handful of potential
point designs. Mission value is often difficult to compare among alternatives because it is
often not captured quantitatively. The framework presented here is unique in its quick and
thorough population of a Pareto front in the mission importance vs. cost domain, allowing
early selection of non-dominated, Pareto-optimal designs. This is achieved via automated
evaluation of thousands of potential candidate architecture and payload combinations. In an
illustration of this method, 70,000 cases are sized for a robotic mission to the near-Earth
asteroid 99942 Apophis. A design on the resulting Pareto front is chosen, and initial mass
and cost estimates returned are accurate within 2-5% compared to the detailed final design.
Despite some limitations, it is concluded that this framework is theoretically extensible to
non-robotic, and perhaps even non-exploration, missions. It is believed that this framework
is a valuable addition to the system engineer's toolbox and that it can allow the selection of
higher-value, lower-cost solutions during preliminary design.
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Date
2007-09
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Text
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Paper
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