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

Yangmin Li, Sio Hong Leong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

18 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)611-621
Number of pages11
JournalRobotica
Volume22
Issue number6
DOIs
Publication statusPublished - 1 Nov 2004
Externally publishedYes

Keywords

  • CMAC neural networks
  • Kinematics
  • Redundant manipulators

ASJC Scopus subject areas

  • Control and Systems Engineering

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