Inverse kinematics solution for trajectory tracking using artificial neural networks for SCORBOT ER-4u

Author

Kumar, Rahul R. ; Chand, Praneel

Author_Institution

Sch. of Eng. & Phys., Univ. of the South Pacific, Suva, Fiji

fYear

2015

fDate

17-19 Feb. 2015

Firstpage

364

Lastpage

369

Abstract

This paper presents the kinematic analysis of the SCORBOT-ER 4u robot arm using a Multi-Layered Feed-Forward (MLFF) Neural Network. The SCORBOT-ER 4u is a 5-DOF vertical articulated educational robot with revolute joints. The Denavit-Hartenberg and Geometrical methods are the forward kinematic algorithms used to generate data and train the neural network. The learning of forward-inverse mapping enables the inverse kinematic solution to be found. The algorithm is tested on hardware (SCORBOT-ER 4u) and reliable results are obtained. The modeling and simulations are done using MATLAB 8.0 software.

Keywords

control engineering computing; manipulator dynamics; manipulator kinematics; multilayer perceptrons; trajectory control; MATLAB 8.0 software; MLFF neural network; SCORBOT-ER 4u robot arm; articulated educational robot; artificial neural network; forward kinematic algorithm; inverse kinematics solution; kinematic analysis; multilayered feed-forward neural network; trajectory tracking; Artificial neural networks; End effectors; Joints; Kinematics; Training; Trajectory; Back-Propagation; Feed-Forward Propagation; Forward Kinematics; Geometrical approach; Inverse Kinematics;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation, Robotics and Applications (ICARA), 2015 6th International Conference on

Conference_Location

Queenstown

Type

conf

DOI

10.1109/ICARA.2015.7081175

Filename

7081175