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UID:dacd8c96-55c7-4f85-815e-06f113cb37a1@nexttoyou
DTSTAMP:20261106T173747Z
DTSTART:20261124T183000Z
DTEND:20261124T193000Z
SUMMARY:MAE Colloquium: Ryne Beeson (Princeton)
LOCATION:Kimball Hall B11
DESCRIPTION:Spacecraft Trajectory Design and Flight with Machine Learning\
 n\nLow thrust propulsion is now a ubiquitous choice of propulsion system 
 for a wide range of space missions\, including in chaotic and complex dyn
 amical environments\, such as the Earth-Moon system. A central difficulty
  of designing for low thrust is the global search problem at high cadence
 \, which requires a balance of modeling fidelity\, continuation approache
 s\, and often highly experienced mission designers. A second difficult ar
 ises in the operation of the mission where unplanned thruster outage even
 ts are likely to occur\, and autonomous re-planning is not yet demonstrat
 ed. In this seminar we will review the progress of research and use of ma
 chine learning in space flight design\, and onboard guidance\, navigation
 \, and control. We show how enabling generative model formulations and ar
 chitectures should be chosen based on the navigation problem of interest 
 and then demonstrate recent results for low thrust mission design and onb
 oard guidance in three-body systems.\n\nBio: Ryne Beeson is an assistant 
 professor of mechanical and aerospace engineering at Princeton University
 . He received his degrees (B.S.\, M.S.\, and Ph.D.) in aerospace engineer
 ing and an M.S. in mathematics from the University of Illinois at Urbana-
 Champaign\, where he was also recognized with the Department of Aerospace
  Engineering’s Kenneth Lee Herrick Memorial Award for outstanding Ph.D. r
 esearch. He was a senior scientist for CU Aerospace L.L.C. in Champ\n\nht
 tp://next-to-u.app/events/dacd8c96-55c7-4f85-815e-06f113cb37a1
URL:http://next-to-u.app/events/dacd8c96-55c7-4f85-815e-06f113cb37a1
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