DocumentCode
2438027
Title
Demonstration of Self-Training Autonomous Neural Networks in Space Vehicle Docking Simulations
Author
Patrick, M. Clinton ; Thaler, Stephen L. ; Stevenson-Chavis, Katherine
Author_Institution
Marshall Space Flight Center, Huntsville
fYear
2007
fDate
3-10 March 2007
Firstpage
1
Lastpage
6
Abstract
Neural 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 paper1,2 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.
Keywords
aerospace computing; aerospace simulation; neural nets; space vehicles; NASA Marshall Space Flight Center; automatic adaptation; autonomous space vehicle docking simulations; computer learning; self-training autonomous neural networks; Artificial neural networks; Engines; Laboratories; NASA; Neural networks; Orbital robotics; Space technology; Space vehicles; Synthetic aperture sonar; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Aerospace Conference, 2007 IEEE
Conference_Location
Big Sky, MT
ISSN
1095-323X
Print_ISBN
1-4244-0524-6
Electronic_ISBN
1095-323X
Type
conf
DOI
10.1109/AERO.2007.352649
Filename
4161527
Link To Document