Optimization of Parallel Manipulators Using Evolutionary Algorithms

  • Manuel R. Barbosa
  • E. J. Solteiro Pires
  • António M. Lopes
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 73)


Parallel manipulators have attracted the attention of researchers from different areas such as: high-precision robotics, machine-tools, simulators and haptic devices. The choice of a particular structural configuration and its dimensioning is a central issue to the performance of these manipulators. A solution to the dimensioning problem, normally involves the definition of performance criteria as part of an optimization process. In this paper the kinematic design of a 6-dof parallel robotic manipulator for maximum dexterity is analyzed. The condition number of the inverse kinematic jacobian is defined as the measure of dexterity and solutions that minimize this criterion are found through a genetic algorithm formulation. Subsequently a neuro-genetic formulation is developed and tested. It is shown that the neuro-genetic algorithm can find close to optimal solutions for maximum dexterity, significantly reducing the computational load.


Parallel Manipulator Kinematic Parameter Haptic Device Kinematic Design Manipulator Workspace 
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 2010

Authors and Affiliations

  • Manuel R. Barbosa
    • 1
  • E. J. Solteiro Pires
    • 2
  • António M. Lopes
    • 1
  1. 1.IDMEC – Pólo FEUPFaculdade de Engenharia da Universidade do PortoPortoPortugal
  2. 2.Centro de Investigação e de Tecnologias Agro-Ambientais e BiológicasEscola de Ciências e Tecnologia da Universidade de Trás-os-Montes e Alto Douro, Quinta de PradosVila RealPortugal

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