Cerebellum-inspired neural network solution of the inverse kinematics problem

The demand today for more complex robots that have manipulators with higher degrees of freedom is increasing because of technological advances. Obtaining the precise movement for a desired trajectory or a sequence of arm and positions requires the computation of the inverse kinematic (IK) function,...

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Main Authors:	Asadi-Eydivand, M., Ebadzadeh, M.M., Solati-Hashjin, M., Darlot, C., Abu Osman, N.A.
Format:	Article
Published:	2015
Subjects:	QA75 Electronic computers. Computer science
Online Access:	DOI: 10.1007/s00422-015-0661-7 DOI: 10.1007/s00422-015-0661-7

id	um-16519
recordtype	eprints
spelling	um-165192016-09-23T02:31:04Z Cerebellum-inspired neural network solution of the inverse kinematics problem Asadi-Eydivand, M. Ebadzadeh, M.M. Solati-Hashjin, M. Darlot, C. Abu Osman, N.A. QA75 Electronic computers. Computer science The demand today for more complex robots that have manipulators with higher degrees of freedom is increasing because of technological advances. Obtaining the precise movement for a desired trajectory or a sequence of arm and positions requires the computation of the inverse kinematic (IK) function, which is a major problem in robotics. The solution of the IK problem leads robots to the precise position and orientation of their end-effector. We developed a bioinspired solution comparable with the cerebellar anatomy and function to solve the said problem. The proposed model is stable under all conditions merely by parameter determination, in contrast to recursive model-based solutions, which remain stable only under certain conditions. We modified the proposed model for the simple two-segmented arm to prove the feasibility of the model under a basic condition. A fuzzy neural network through its learning method was used to compute the parameters of the system. Simulation results show the practical feasibility and efficiency of the proposed model in robotics. The main advantage of the proposed model is its generalizability and potential use in any robot. 2015 Article PeerReviewed DOI: 10.1007/s00422-015-0661-7 Asadi-Eydivand, M.; Ebadzadeh, M.M.; Solati-Hashjin, M.; Darlot, C.; Abu Osman, N.A. (2015) Cerebellum-inspired neural network solution of the inverse kinematics problem. Biological Cybernetics <http://eprints.um.edu.my/view/publication/Biological_Cybernetics_.html>, 109 (6). pp. 561-574. ISSN 0340-1200 http://eprints.um.edu.my/16519/
repository_type	Digital Repository
institution_category	Local University
institution	University Malaya
building	UM Research Repository
collection	Online Access
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Asadi-Eydivand, M. Ebadzadeh, M.M. Solati-Hashjin, M. Darlot, C. Abu Osman, N.A. Cerebellum-inspired neural network solution of the inverse kinematics problem
description	The demand today for more complex robots that have manipulators with higher degrees of freedom is increasing because of technological advances. Obtaining the precise movement for a desired trajectory or a sequence of arm and positions requires the computation of the inverse kinematic (IK) function, which is a major problem in robotics. The solution of the IK problem leads robots to the precise position and orientation of their end-effector. We developed a bioinspired solution comparable with the cerebellar anatomy and function to solve the said problem. The proposed model is stable under all conditions merely by parameter determination, in contrast to recursive model-based solutions, which remain stable only under certain conditions. We modified the proposed model for the simple two-segmented arm to prove the feasibility of the model under a basic condition. A fuzzy neural network through its learning method was used to compute the parameters of the system. Simulation results show the practical feasibility and efficiency of the proposed model in robotics. The main advantage of the proposed model is its generalizability and potential use in any robot.
format	Article
author	Asadi-Eydivand, M. Ebadzadeh, M.M. Solati-Hashjin, M. Darlot, C. Abu Osman, N.A.
author_facet	Asadi-Eydivand, M. Ebadzadeh, M.M. Solati-Hashjin, M. Darlot, C. Abu Osman, N.A.
author_sort	Asadi-Eydivand, M.
title	Cerebellum-inspired neural network solution of the inverse kinematics problem
title_short	Cerebellum-inspired neural network solution of the inverse kinematics problem
title_full	Cerebellum-inspired neural network solution of the inverse kinematics problem
title_fullStr	Cerebellum-inspired neural network solution of the inverse kinematics problem
title_full_unstemmed	Cerebellum-inspired neural network solution of the inverse kinematics problem
title_sort	cerebellum-inspired neural network solution of the inverse kinematics problem
publishDate	2015
url	DOI: 10.1007/s00422-015-0661-7 DOI: 10.1007/s00422-015-0661-7
first_indexed	2018-09-06T06:37:56Z
last_indexed	2018-09-06T06:37:56Z
_version_	1610839098711343104

Cerebellum-inspired neural network solution of the inverse kinematics problem

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