Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1797
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dc.contributor.authorJha, P-
dc.contributor.authorBiswal, B B-
dc.date.accessioned2012-12-19T10:34:48Z-
dc.date.available2012-12-19T10:34:48Z-
dc.date.issued2012-12-
dc.identifier.citation4th International & 25th All India Machine Tool Design and Research (AIMTDR) Conference – 2012 , Jadavpur University, Kolkataen
dc.identifier.urihttp://hdl.handle.net/2080/1797-
dc.descriptionCopyright for this paper belongs to proceeding publisheren
dc.description.abstractInverse kinematics comprises the computation need to find the joint angles for a given Cartesian position and orientation of the end effectors. There is no unique solution for the inverse kinematics thus necessitating application of artificial neural network models. This paper proposes three different types of structured artificial neural network (ANN) models to find the solution of inverse kinematics. The first one is an ANN model which is MLP (multi-layer perceptron’s) and is popular as back propagation neural network model. In this gradient descent type of learning rules are applied. The second kind of ANN model is PPN (polynomial poly-processor neural network) where polynomial equation is used and the last one is Pi-network.en
dc.format.extent627649 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.subjectRobot manipulatoren
dc.subjectInverse kinematicsen
dc.subjectneural networken
dc.titleDevelopment of an intelligent system for prediction of inverse kinematics of robot manipulatoren
dc.typeArticleen
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