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A Simulation of 6R Industrial Articulated Robot Arm Using Neural Network
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Author(s)
Manigpan, Supachoke
Other Contributor(s)
University of the Thai Chamber of Commerce. Graduate School
Publisher(s)
University of the Thai Chamber of Commerce
Date Issued
2010
Resource Type
Master thesis
Language
English
Abstract
This 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.
Subject(s)
Degree Level
masters
Degree Department
School of Engineering
Degree Grantor
University of the Thai Chamber of Commerce
Access Rights
Open access
Rights
This work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner.
Rights Holder
University of the Thai Chamber of Commerce
Bibliographic Citation
Supachoke Manigpan (2010) A Simulation of 6R Industrial Articulated Robot Arm Using Neural Network.
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