Please use this identifier to cite or link to this item: https://scholar.utcc.ac.th/handle/6626976254/1302
Title: A Simulation of 6R Industrial Articulated Robot Arm Using Neural Network
Authors: Manigpan, Supachoke 
Issue Date: 2010
Publisher: University of the Thai Chamber of Commerce
Source: Supachoke Manigpan (2010) A Simulation of 6R Industrial Articulated Robot Arm Using Neural Network.
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.
URI: https://scholar.utcc.ac.th/handle/6626976254/1302
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.
Appears in Collections:GS: Theses / Independent Studies

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