Please use this identifier to cite or link to this item: https://scholar.utcc.ac.th/handle/6626976254/1302
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dc.contributor.authorManigpan, Supachoke
dc.contributor.otherUniversity of the Thai Chamber of Commerce. Graduate School
dc.date.accessioned2018-09-13T09:58:02Z-
dc.date.available2018-09-13T09:58:02Z-
dc.date.issued2010
dc.identifier.citationSupachoke Manigpan (2010) A Simulation of 6R Industrial Articulated Robot Arm Using Neural Network.
dc.identifier.urihttps://scholar.utcc.ac.th/handle/6626976254/1302-
dc.description.abstractThis paper presents a simulation of a 6 degrees-of-freedom (6R) articulatedrobot arm using back propagation neural network to solve the problem regardinginverse kinematics for the industrial articulated robot. The Denavit – Hartenberg modelis used to analyze the robot arm movement. Next, the forward kinematics is used toidentify the relationships for each joint of the robot arm and to determine variousparameters for learning system of random neural network for 5,000 data points. Thesimulation results show that the robot arm can move to target positions with precision,and the average error for the entire 6 joints is at approximately 4.03 degrees.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherUniversity of the Thai Chamber of Commerce
dc.rightsThis work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner.
dc.subject.otherComputer and Multimedia Engineering
dc.titleA Simulation of 6R Industrial Articulated Robot Arm Using Neural Network
dc.typeThesis
dcterms.accessRightspublic
dc.rights.holderUniversity of the Thai Chamber of Commerce
thesis.degree.departmentSchool of Engineering
thesis.degree.grantorUniversity of the Thai Chamber of Commerce
thesis.degree.levelmasters
utcc.eprintid2759
Appears in Collections:GS: Theses / Independent Studies
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