Persistent Link:
http://hdl.handle.net/10150/613800
Title:
THE APPLICATION OF NEURAL NETWORKS TO DRONE CONTROL
Author:
Greenwood, Dan
Affiliation:
NETROLOGIC, Inc.
Issue Date:
1990-11
Rights:
Copyright © International Foundation for Telemetering
Collection Information:
Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.
Publisher:
International Foundation for Telemetering
Journal:
International Telemetering Conference Proceedings
Abstract:
The FAA Sponsored a six months research program to investigate the application of neural networks to controlling aircraft. It was found that properly configured neural networks offer powerful new computationally robust methods to generate command vectors corresponding to collision free routes. Methods using neural networks which capture the expertise employed by controllers in resolving conflicts were formed. This paper shows that many of the neural network techniques applied to ATC can also be applied to drone control. Two different networks are presented: a multi-layer feed-forward network using back-propagation and a method using a potential field where a gradient measure is employed to maintain the aircraft separation in real time.
Sponsors:
International Foundation for Telemetering
ISSN:
0884-5123; 0074-9079
Additional Links:
http://www.telemetry.org/

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleTHE APPLICATION OF NEURAL NETWORKS TO DRONE CONTROLen_US
dc.contributor.authorGreenwood, Danen
dc.contributor.departmentNETROLOGIC, Inc.en
dc.date.issued1990-11-
dc.rightsCopyright © International Foundation for Telemeteringen
dc.description.collectioninformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.en
dc.publisherInternational Foundation for Telemeteringen
dc.description.abstractThe FAA Sponsored a six months research program to investigate the application of neural networks to controlling aircraft. It was found that properly configured neural networks offer powerful new computationally robust methods to generate command vectors corresponding to collision free routes. Methods using neural networks which capture the expertise employed by controllers in resolving conflicts were formed. This paper shows that many of the neural network techniques applied to ATC can also be applied to drone control. Two different networks are presented: a multi-layer feed-forward network using back-propagation and a method using a potential field where a gradient measure is employed to maintain the aircraft separation in real time.en
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.identifier.issn0884-5123-
dc.identifier.issn0074-9079-
dc.identifier.urihttp://hdl.handle.net/10150/613800-
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.typetexten
dc.typeProceedingsen
dc.relation.urlhttp://www.telemetry.org/en
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