Inverse kinematics of an equal length links planar hyper redundant manipulator using neural networks

An iterative method using the neural networks to solve the inverse kinematics problem for equal length links redundant manipulators is presented in this paper. The training phase, calculating the neural networks weights, is accomplished for a new proposed geometrical method to solve the problem of m...

Full description

Bibliographic Details
Main Authors: Yahya, S., Mohamed, H.A.F., Moghavvemi, M., Yang, S.S.
Format: Conference or Workshop Item
Published: 2009
Subjects:
_version_ 1825719752744501248
author Yahya, S.
Mohamed, H.A.F.
Moghavvemi, M.
Yang, S.S.
author_facet Yahya, S.
Mohamed, H.A.F.
Moghavvemi, M.
Yang, S.S.
author_sort Yahya, S.
collection UM
description An iterative method using the neural networks to solve the inverse kinematics problem for equal length links redundant manipulators is presented in this paper. The training phase, calculating the neural networks weights, is accomplished for a new proposed geometrical method to solve the problem of multi-solution caused by redundancy. The use of this geometrical method results in one solution among the infinite solutions of the inverse kinematics of the redundant manipulators. This method is very effective for avoiding the singularity problem because it guarantees that there is no lining up for two or more links. Another advantage for this method is that the angles between the links will be set between two maximum and minimum values. This means that the end-effecter can reach any point on the desired path and the angles between the links will not be less than the minimum limit or more than the maximum limit, which makes this method effective for joint limits. To demonstrate the effectiveness of this proposed method, experiments were conducted on an 8 links hyper redundant manipulator in this paper. In addition, the workspace of the manipulator is calculated for this proposed method.
first_indexed 2024-03-06T05:24:34Z
format Conference or Workshop Item
id um.eprints-9718
institution Universiti Malaya
last_indexed 2024-03-06T05:24:34Z
publishDate 2009
record_format dspace
spelling um.eprints-97182017-11-23T02:25:01Z http://eprints.um.edu.my/9718/ Inverse kinematics of an equal length links planar hyper redundant manipulator using neural networks Yahya, S. Mohamed, H.A.F. Moghavvemi, M. Yang, S.S. TA Engineering (General). Civil engineering (General) An iterative method using the neural networks to solve the inverse kinematics problem for equal length links redundant manipulators is presented in this paper. The training phase, calculating the neural networks weights, is accomplished for a new proposed geometrical method to solve the problem of multi-solution caused by redundancy. The use of this geometrical method results in one solution among the infinite solutions of the inverse kinematics of the redundant manipulators. This method is very effective for avoiding the singularity problem because it guarantees that there is no lining up for two or more links. Another advantage for this method is that the angles between the links will be set between two maximum and minimum values. This means that the end-effecter can reach any point on the desired path and the angles between the links will not be less than the minimum limit or more than the maximum limit, which makes this method effective for joint limits. To demonstrate the effectiveness of this proposed method, experiments were conducted on an 8 links hyper redundant manipulator in this paper. In addition, the workspace of the manipulator is calculated for this proposed method. 2009-08 Conference or Workshop Item PeerReviewed Yahya, S. and Mohamed, H.A.F. and Moghavvemi, M. and Yang, S.S. (2009) Inverse kinematics of an equal length links planar hyper redundant manipulator using neural networks. In: ICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009, 18-21 August 2009, Fukuoka, Japan.
spellingShingle TA Engineering (General). Civil engineering (General)
Yahya, S.
Mohamed, H.A.F.
Moghavvemi, M.
Yang, S.S.
Inverse kinematics of an equal length links planar hyper redundant manipulator using neural networks
title Inverse kinematics of an equal length links planar hyper redundant manipulator using neural networks
title_full Inverse kinematics of an equal length links planar hyper redundant manipulator using neural networks
title_fullStr Inverse kinematics of an equal length links planar hyper redundant manipulator using neural networks
title_full_unstemmed Inverse kinematics of an equal length links planar hyper redundant manipulator using neural networks
title_short Inverse kinematics of an equal length links planar hyper redundant manipulator using neural networks
title_sort inverse kinematics of an equal length links planar hyper redundant manipulator using neural networks
topic TA Engineering (General). Civil engineering (General)
work_keys_str_mv AT yahyas inversekinematicsofanequallengthlinksplanarhyperredundantmanipulatorusingneuralnetworks
AT mohamedhaf inversekinematicsofanequallengthlinksplanarhyperredundantmanipulatorusingneuralnetworks
AT moghavvemim inversekinematicsofanequallengthlinksplanarhyperredundantmanipulatorusingneuralnetworks
AT yangss inversekinematicsofanequallengthlinksplanarhyperredundantmanipulatorusingneuralnetworks