Sooho Park

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—In recent years, robots have been increasingly utilized in applications with complex unknown environments, which makes system modeling challenging. In order to meet the demand from such applications, an experience-based learning approach can be used. In this paper, a novel learning algorithm is proposed, which can learn an unknown system model from given(More)
Using a scenario of multiple mobile observing platforms (UAVs) measuring weather variables in distributed regions of the Pacific, we are developing algorithms that will lead to improved forecasting of high-impact weather events. We combine technologies from the nonlinear weather prediction and plan-ning/control communities to create a close link between(More)
Human adenovirus type 36 (Ad36) as an obesity agent induces adiposity by increasing glucose uptake and promoting chronic inflammation in fat tissues; in contrast, exercise reduces total body fat and inflammation. Our objective was to determine the association between Ad36 and the effects of exercise on inflammation and glycemic control. In the human trials(More)
This work addresses the problem of trajectory planning for UAV sensors taking measurements of a large nonlinear system to improve estimation and prediction of such a system. The lack of perfect knowledge of the global system state typically requires probabilistic state estimation. The goal is therefore to find trajectories such that the measurements along(More)
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