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dc.contributor.authorYoung, KYen_US
dc.contributor.authorChen, JJen_US
dc.date.accessioned2014-12-08T15:46:43Z-
dc.date.available2014-12-08T15:46:43Z-
dc.date.issued1999-04-01en_US
dc.identifier.issn0921-0296en_US
dc.identifier.urihttp://dx.doi.org/10.1023/A:1008094014724en_US
dc.identifier.urihttp://hdl.handle.net/11536/31419-
dc.description.abstractCurrent robot calibration schemes usually employ calibration models with constant error parameters. Consequently, they are inevitably subject to a certain degree of locality, i.e., the calibrated error parameters (CEPs) will produce the desired accuracy only in certain regions of the robot workspace. To deal with the locality phenomenon, CEPs that vary in different regions of the robot workspace may be more appropriate. Hence, we propose a variable D-H (Denavit and Hartenberg) parameter model to formulate variations of CEPs. An FCMAC (Fuzzy Cerebellar Model Articulation Controller) learning algorithm is used to implement the proposed variable D-K parameter model. Simulations and experiments that verify the effectiveness of the proposed calibration scheme based on the variable D-H parameter model are described.en_US
dc.language.isoen_USen_US
dc.subjectrobot calibrationen_US
dc.subjectvariable D-H parameter modelen_US
dc.subjectFCMAC learning algorithmen_US
dc.titleImplementation of a variable D-H parameter model for robot calibration using an FCMAC learning algorithmen_US
dc.typeArticleen_US
dc.identifier.doi10.1023/A:1008094014724en_US
dc.identifier.journalJOURNAL OF INTELLIGENT & ROBOTIC SYSTEMSen_US
dc.citation.volume24en_US
dc.citation.issue4en_US
dc.citation.spage313en_US
dc.citation.epage346en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000079722900001-
dc.citation.woscount6-
Appears in Collections:Articles


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