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Demonstration of Self-Training Autonomous Neural Networks in Space Vehicle Docking SimulationsNeural Networks have been under examination for decades in many areas of research, with varying degrees of success and acceptance. Key goals of computer learning, rapid problem solution, and automatic adaptation have been elusive at best. This paper summarizes efforts at NASA's Marshall Space Flight Center harnessing such technology to autonomous space vehicle docking for the purpose of evaluating applicability to future missions.
Document ID
Acquisition Source
Marshall Space Flight Center
Document Type
Conference Paper
Patrick, M. Clinton
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Thaler, Stephen L.
(Imagination Engines, Inc. Saint Louis, MO, United States)
Stevenson-Chavis, Katherine
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Date Acquired
August 23, 2013
Publication Date
December 28, 2006
Subject Category
Spacecraft Design, Testing And Performance
Report/Patent Number
IEEEAC Ppaper 1409
Meeting Information
Meeting: 2007 IEEE Aerospace Conference
Location: Big Sky, MT
Country: United States
Start Date: March 3, 2007
End Date: March 10, 2007
Sponsors: Institute of Electrical and Electronics Engineers
Distribution Limits
Public Use Permitted.
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