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DTSTART;TZID=America/New_York:20240626T130000
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DTSTAMP:20260603T120846
CREATED:20240621T123059Z
LAST-MODIFIED:20240621T123059Z
UID:11628-1719406800-1719406800@seasevents.nmsdev7.com
SUMMARY:ESE Ph.D. Thesis Defense: "Mobile Mission Planning in Uncertain Environments"
DESCRIPTION:Robotic mission planning in uncertain environments remains a formidable challenge due to environmental complexity and sensor noise. This dissertation introduces new methodologies to tackle these issues. We develop a method for Linear Temporal Logic (LTL) planning\, extending it to completely unknown environments to enable dynamic understanding and task fulfillment. Large language models (LLMs) are also leveraged to make task expression more user-friendly and to exploit their reasoning capabilities to improve mission planning while maintaining the guarantees from traditional LTL planning. For multi-robot systems\, I focus on enhancing scalability and coordination using Graph Neural Networks (GNNs) for distributed\, non-myopic active information gathering. I validate the resulting algorithms with several numerical simulations.
URL:https://seasevents.nmsdev7.com/event/ese-ph-d-thesis-defense-mobile-mission-planning-in-uncertain-environments/
LOCATION:Berger Auditorium (Room 13)\, Skirkanich Hall\, 210 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Dissertation or Thesis Defense
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
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