Geometrically Bounded Singularities and Joint Limits Prevention of a Three Dimensional Planar Redundant Manipulator Using Artificial Neural Networks

  • Samer Yahya
  • Mahmoud Moghavvemi
  • Haider Abbas F. Almurib
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 304)

Abstract

This paper presents an Artificial Neural Network (ANN) based on the nonlinear dynamical control of a three-dimensional six degrees of freedom planar redundant manipulator. An ANN controller is used for the computation of fast inverse kinematics, and is effective on geometrically bounded singularities and joint limits prevention of redundant manipulators. The radial basis function neural network has been used to estimate the centrifugal and gravitational effects of the joints, when the end-effector follows a desired path.

Keywords

Artificial Neural Network Radial Basis Function Neural Network Joint Limit Redundant Manipulator Singularity Avoidance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Samer Yahya
    • 1
  • Mahmoud Moghavvemi
    • 1
    • 2
  • Haider Abbas F. Almurib
    • 3
  1. 1.Center of Research in Applied Electronics (CRAE)University of MalayaKuala LumpurMalaysia
  2. 2.Faculty of Electrical and Computer EngineeringUniversity of TehranIran
  3. 3.Department of Electrical & Electronic EngineeringThe University of Nottingham Malaysia CampusMalaysia

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