Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-10T20:57:28.711Z Has data issue: false hasContentIssue false
  • English
  • Français

Kinematics control of redundant manipulators using a CMAC neural network combined with a genetic algorithm

Published online by Cambridge University Press:  15 November 2004

Yangmin Li  and
Sio Hong Leong
Yangmin Li
Affiliation:
Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Av. Padre Tomás Pereira S.J., Taipa, Macau SAR (P.R.China)
Sio Hong Leong
Affiliation:
Department of Electromechanical Engineering, Faculty of Science and Technology, University of Macau, Av. Padre Tomás Pereira S.J., Taipa, Macau SAR (P.R.China)
Get access Rights & Permissions [Opens in a new window]

Abstract

A method is proposed to solve the inverse kinematics and control problems of robot control systems using a cerebellar model articulation controller neural network combined with a genetic algorithm. Computer simulations and experiments with a 7-DOF redundant modular manipulator have demonstrated the effectiveness of the proposed method.

Keywords

Redundant manipulatorsKinematicsCMAC neural networks
Type
Research Article
Information
Robotica , Volume 22 , Issue 6 , November 2004 , pp. 611 - 621
Copyright
© 2004 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)