Development of Artificial Intelligent Techniques for Manipulator Position Control

Inspired by works in soft computing this research applies the constituents of soft computing to act as the "brain" that controls the positioning process of a robot manipulator's tool. This work combines three methods in artificial intelligence: fuzzy rules, neural networks, and gen...

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Main Author: Bani Hashim, Ahmad Yusairi
Format: Thesis
Language:English
English
Published: 2002
Online Access:http://psasir.upm.edu.my/id/eprint/10649/1/FK_2002_18.pdf
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author Bani Hashim, Ahmad Yusairi
author_facet Bani Hashim, Ahmad Yusairi
author_sort Bani Hashim, Ahmad Yusairi
collection UPM
description Inspired by works in soft computing this research applies the constituents of soft computing to act as the "brain" that controls the positioning process of a robot manipulator's tool. This work combines three methods in artificial intelligence: fuzzy rules, neural networks, and genetic algorithm to form the soft computing plant uniquely planned for a six degree-of-freedom serial manipulator. The forward kinematics of the manipulator is made as the feedforward control plant while the soft computing plant replaces the inverse kinematics in the feedback loop. Fine manipulator positioning is first achieved from the learning stage, and later execution through forward kinematics after the soft computing plant proposes inputs and the iterations. It is shown experimentally that the technique proposed is capable of producing results with very low errors. Experiment A for example resulted the position errors onpx: 0.004%;py: 0.006%; andpz: 0.002%.
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spelling upm.eprints-106492024-05-08T00:53:10Z http://psasir.upm.edu.my/id/eprint/10649/ Development of Artificial Intelligent Techniques for Manipulator Position Control Bani Hashim, Ahmad Yusairi Inspired by works in soft computing this research applies the constituents of soft computing to act as the "brain" that controls the positioning process of a robot manipulator's tool. This work combines three methods in artificial intelligence: fuzzy rules, neural networks, and genetic algorithm to form the soft computing plant uniquely planned for a six degree-of-freedom serial manipulator. The forward kinematics of the manipulator is made as the feedforward control plant while the soft computing plant replaces the inverse kinematics in the feedback loop. Fine manipulator positioning is first achieved from the learning stage, and later execution through forward kinematics after the soft computing plant proposes inputs and the iterations. It is shown experimentally that the technique proposed is capable of producing results with very low errors. Experiment A for example resulted the position errors onpx: 0.004%;py: 0.006%; andpz: 0.002%. 2002-10 Thesis NonPeerReviewed text en http://psasir.upm.edu.my/id/eprint/10649/1/FK_2002_18.pdf Bani Hashim, Ahmad Yusairi (2002) Development of Artificial Intelligent Techniques for Manipulator Position Control. Masters thesis, Universiti Putra Malaysia. English
spellingShingle Bani Hashim, Ahmad Yusairi
Development of Artificial Intelligent Techniques for Manipulator Position Control
title Development of Artificial Intelligent Techniques for Manipulator Position Control
title_full Development of Artificial Intelligent Techniques for Manipulator Position Control
title_fullStr Development of Artificial Intelligent Techniques for Manipulator Position Control
title_full_unstemmed Development of Artificial Intelligent Techniques for Manipulator Position Control
title_short Development of Artificial Intelligent Techniques for Manipulator Position Control
title_sort development of artificial intelligent techniques for manipulator position control
url http://psasir.upm.edu.my/id/eprint/10649/1/FK_2002_18.pdf
work_keys_str_mv AT banihashimahmadyusairi developmentofartificialintelligenttechniquesformanipulatorpositioncontrol