Improved approach to the solution of inverse kinematics problems for robot manipulators

Simple item page
dc.contributor.authorKarlik B.
dc.contributor.authorAydin S.
dc.date.accessioned2024-07-22T08:25:40Z
dc.date.available2024-07-22T08:25:40Z
dc.date.issued2000
dc.description.abstractA structured artificial neural-network (ANN) approach has been proposed here to control the motion of a robot manipulator. Many neural-network models use threshold units with sigmoid transfer functions and gradient descent-type learning rules. The learning equations used are those of the backpropagation algorithm. In this work, the solution of the kinematics of a six-degrees-of-freedom robot manipulator is implemented by using ANN. Work has been undertaken to find the best ANN configurations for this problem. Both the placement and orientation angles of a robot manipulator are used to fin the inverse kinematics solutions.
dc.identifier.DOI-ID10.1016/S0952-1976(99)00050-0
dc.identifier.issn09521976
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/20543
dc.language.isoEnglish
dc.publisherElsevier Science Ltd
dc.subjectBackpropagation
dc.subjectDegrees of freedom (mechanics)
dc.subjectIntelligent control
dc.subjectInverse kinematics
dc.subjectInverse problems
dc.subjectLearning algorithms
dc.subjectLearning systems
dc.subjectManipulators
dc.subjectMathematical models
dc.subjectMotion control
dc.subjectProblem solving
dc.subjectTransfer functions
dc.subjectStructured artificial neural networks
dc.subjectNeural networks
dc.titleImproved approach to the solution of inverse kinematics problems for robot manipulators
dc.typeArticle

Files

Collections

Scopus Koleksiyonu