Predicting the motion of a robot manipulator with unknown trajectories based on artificial neural network

Mathematically, the motion of a robot manipulator can be computed through the integration of kinematics, dynamics, and trajectories calculations. However, the calculations are complex and only can be applied if the configuration of the robot and the characteristics of the joint trajectories are know...

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Main Authors: Tang, Sai Hong, Ang, Chun Kit, Mohd Arrifin, Mohd Khairol Anuar, Mashohor, Syamsiah
Format: Article
Language:English
Published: InTech Open Access Publisher 2014
Online Access:http://psasir.upm.edu.my/id/eprint/34991/
http://psasir.upm.edu.my/id/eprint/34991/1/34991.pdf
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author Tang, Sai Hong
Ang, Chun Kit
Mohd Arrifin, Mohd Khairol Anuar
Mashohor, Syamsiah
author_facet Tang, Sai Hong
Ang, Chun Kit
Mohd Arrifin, Mohd Khairol Anuar
Mashohor, Syamsiah
author_sort Tang, Sai Hong
building UPM Institutional Repository
collection Online Access
description Mathematically, the motion of a robot manipulator can be computed through the integration of kinematics, dynamics, and trajectories calculations. However, the calculations are complex and only can be applied if the configuration of the robot and the characteristics of the joint trajectories are known. This paper introduces the use of artificial neural networks (ANN) to overcome these shortcomings by solving nonlinear functions and adapting the characteristics of unknown trajectories. A virtual six-degree-of-freedom (DOF) robot manipulator is exploited as an example to show the robustness of the developed ANN topology.
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spelling upm-349912017-10-30T08:01:22Z http://psasir.upm.edu.my/id/eprint/34991/ Predicting the motion of a robot manipulator with unknown trajectories based on artificial neural network Tang, Sai Hong Ang, Chun Kit Mohd Arrifin, Mohd Khairol Anuar Mashohor, Syamsiah Mathematically, the motion of a robot manipulator can be computed through the integration of kinematics, dynamics, and trajectories calculations. However, the calculations are complex and only can be applied if the configuration of the robot and the characteristics of the joint trajectories are known. This paper introduces the use of artificial neural networks (ANN) to overcome these shortcomings by solving nonlinear functions and adapting the characteristics of unknown trajectories. A virtual six-degree-of-freedom (DOF) robot manipulator is exploited as an example to show the robustness of the developed ANN topology. InTech Open Access Publisher 2014 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/34991/1/34991.pdf Tang, Sai Hong and Ang, Chun Kit and Mohd Arrifin, Mohd Khairol Anuar and Mashohor, Syamsiah (2014) Predicting the motion of a robot manipulator with unknown trajectories based on artificial neural network. International Journal of Advanced Robotic Systems, 11. art. no. 176. pp. 1-9. ISSN 1729-8814; ESSN: 1729-8806 http://www.intechopen.com/journals/howtoreference/international_journal_of_advanced_robotic_systems/predicting-the-motion-of-a-robot-manipulator-with-unknown-trajectories-based-on-an-artificial-neural 10.5772/59278
spellingShingle Tang, Sai Hong
Ang, Chun Kit
Mohd Arrifin, Mohd Khairol Anuar
Mashohor, Syamsiah
Predicting the motion of a robot manipulator with unknown trajectories based on artificial neural network
title Predicting the motion of a robot manipulator with unknown trajectories based on artificial neural network
title_full Predicting the motion of a robot manipulator with unknown trajectories based on artificial neural network
title_fullStr Predicting the motion of a robot manipulator with unknown trajectories based on artificial neural network
title_full_unstemmed Predicting the motion of a robot manipulator with unknown trajectories based on artificial neural network
title_short Predicting the motion of a robot manipulator with unknown trajectories based on artificial neural network
title_sort predicting the motion of a robot manipulator with unknown trajectories based on artificial neural network
url http://psasir.upm.edu.my/id/eprint/34991/
http://psasir.upm.edu.my/id/eprint/34991/
http://psasir.upm.edu.my/id/eprint/34991/
http://psasir.upm.edu.my/id/eprint/34991/1/34991.pdf