L. Mainini

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A self-aware aerospace vehicle can dynamically adapt the way it performs missions by gathering information about itself and its surroundings and responding intelligently. We consider the specific challenge of an unmanned aerial vehicle that can dynamically and autonomously sense its structural state and re-plan its mission according to its estimated current(More)
This paper proposes a data-driven strategy to assist online rapid decision-making for an unmanned aerial vehicle that uses sensed data to estimate its structural state, uses this estimate to update its corresponding flight capabilities, and then dynamically re-plans its mission accordingly. Our approach comprises offline and online computational phases(More)
The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Abstract In this paper we develop initial offline and online capabilities for a self-aware aerospace vehicle. Such a vehicle can dynamically adapt the way it performs missions by gathering information about itself and its surroundings via(More)
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