Training an artificial neural network the pure pursuit maneuver

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dc.citation.epage353en_US
dc.citation.issueNumber4en_US
dc.citation.spage343en_US
dc.citation.volumeNumber18en_US
dc.contributor.authorHommertzheim, D.en_US
dc.contributor.authorHuffman, J.en_US
dc.contributor.authorSabuncuoglu, Ihsanen_US
dc.date.accessioned2016-02-08T10:56:13Z
dc.date.available2016-02-08T10:56:13Z
dc.date.issued1991en_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.description.abstractArtificial neural networks' ability to learn, categorize, generalize and self organize make them potentially very useful for a variety of application areas. This paper discusses some experiences in attempting to teach a neural network how to perform the pure pursuit maneuver. Several problems were encountered in defining a proper training set. Three and four layer backpropagation networks were utilized to capture the input to output mappings.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:56:13Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 1991en
dc.identifier.doi10.1016/0305-0548(91)90095-9en_US
dc.identifier.issn0305-0548
dc.identifier.urihttp://hdl.handle.net/11693/26187
dc.language.isoEnglishen_US
dc.publisherPergamon Pressen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/0305-0548(91)90095-9en_US
dc.source.titleComputers and Operations Researchen_US
dc.subjectMaps and mappingen_US
dc.subjectPure pursuit maneuversen_US
dc.subjectNeural networksen_US
dc.titleTraining an artificial neural network the pure pursuit maneuveren_US
dc.typeArticleen_US

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