Intelligent control for avoiding the joint limits of redundant planar manipulators

Samy F.M. Assal, Keigo Watanabe, Kiyotaka Izumi

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

This article presents an intelligent control system for a redundant manipulator to avoid physical limits such as joint angle limits and joint velocity limits. In this method, a back-propagation neural network (NN) is introduced for the kinematic inversion of the manipulator. Since this inverse kinematics has an infinite number of joint angle vectors, a fuzzy-neuro system is constructed to provide an approximate value for that vector. This vector is fed into the NN as a hint input vector in order to guide the output of the NN within the self-motion. Simulations and a comparative study are made based on a four-link redundant manipulator to prove the efficacy of the proposed control system.

Original languageEnglish
Pages (from-to)141-148
Number of pages8
JournalArtificial Life and Robotics
Volume10
Issue number2
DOIs
Publication statusPublished - Nov 1 2006
Externally publishedYes

Keywords

  • Fuzzy-neuro system
  • Inverse kinematics
  • Joint limits
  • Neural networks
  • Redundant manipulators

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence

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