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CREATED:20250718T134733Z
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SUMMARY:ESE Fall Seminar - "Distributional Control: From Robotic Motion Planning to Generative AI"
DESCRIPTION:Uncertainty propagation and mitigation is at the core of all robotic and control systems. The standard approach so far has followed the spirit of controlling a system “with uncertainties\,” as opposed to the direct control “of uncertainties.” Borrowing ideas from the classical Optimal Mass Transport (OMT) and Schrödinger Bridge problems\, distributional control has recently emerged as a principled approach to characterize and mitigate uncertainty in stochastic systems with strict performance guarantees. In this talk\, I will review some recent results on covariance and distribution control for stochastic systems subject to chance constraints\, including data-driven and distributionally robust implementations; I will demonstrate the application of the theory to a variety of problems ranging from model predictive control\, robot motion planning under uncertainty\, multi-agent mean-field control\, and generative AI.
URL:https://seasevents.nmsdev7.com/event/ese-fall-seminar-title-tba-3/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
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