dc.contributor.author
Cuevas, Erik V.
dc.contributor.author
Zaldivar, Daniel
dc.contributor.author
Rojas, Raúl
dc.date.accessioned
2018-06-08T07:50:17Z
dc.date.available
2009-05-13T09:28:06.883Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/18814
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-22498
dc.description.abstract
In the robotics area, visual tracking is an important and difficult problem
therefore is necessary to have a robust and efficient control algorithm which
presents immunity characteristics to stochastic direction and speed changes of
the object to be tracked. Also is important count with a segmentation
algorithm which be able to tolerate changes in the intensity of light. We
describe in this report the implementation of fuzzy controllers based on the
fuzzy condensed algorithm and also the developed of a LVQ neural network to
segment the image. For this work we used two fuzzy condensed algorithms
running in a PC to control a robot’s head which tracks a human face. We
describe the main lines of the fuzzy condensed algorithm as well as the LVQ
neural networks architecture employed and the implementation, the fuzzy
condensed controller performance in comparison to a PID controller and real
time results.
de
dc.relation.ispartofseries
urn:nbn:de:kobv:188-fudocsseries000000000021-2
dc.rights.uri
http://www.fu-berlin.de/sites/refubium/rechtliches/Nutzungsbedingungen
dc.subject.ddc
000 Informatik, Informationswissenschaft, allgemeine Werke::000 Informatik, Wissen, Systeme::004 Datenverarbeitung; Informatik
dc.title
Intelligent tracking
refubium.affiliation
Mathematik und Informatik
de
refubium.affiliation.other
Institut für Informatik
refubium.mycore.fudocsId
FUDOCS_document_000000001922
refubium.resourceType.isindependentpub
no
refubium.series.name
Freie Universität Berlin, Fachbereich Mathematik und Informatik
refubium.series.reportNumber
03-15
refubium.mycore.derivateId
FUDOCS_derivate_000000000395
dcterms.accessRights.openaire
open access