Advertisement

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)

Abstract

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.

Keywords

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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Chablat, D., Wenger, P., Majou, F., et al.: An Interval Analysis Based Study for the Design and the Comparison of Three-Degrees-of-Freedom Parallel Kinematic Machines. Int. J. Robot Res. 23, 615–624 (2004)CrossRefGoogle Scholar
  2. 2.
    Lopes, A.M.: Optimization of a 6-DOF Parallel Robotic Manipulator based on Kinematic Performance Indexes. In: Proc. of the 26th IASTED Int. Conf. on Modelling, Identification, and Control, Innsbruck, Austria (2007)Google Scholar
  3. 3.
    Miller, K.: Optimal Design and Modeling of Spatial Parallel Manipulators. Int. J. Robot Res. 23, 127–140 (2004)CrossRefGoogle Scholar
  4. 4.
    Liu, X.-J., Wang, J., Pritschow, G.: Performance atlases and optimum design of planar 5R symmetrical parallel mechanisms. Mech. Mach. Theory 41, 119–144 (2006)zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Alici, G., Shirinzadeh, B.: Optimum synthesis of planar parallel manipulators based on kinematic isotropy and force balancing. Robotica 22, 97–108 (2004)CrossRefGoogle Scholar
  6. 6.
    Rao, N., Rao, K.: Dimensional synthesis of a spatial 3-RPS parallel manipulator for a prescribed range of motion of spherical joints. Mech. Mach. Theory 44, 477–486 (2009)zbMATHCrossRefGoogle Scholar
  7. 7.
    Merlet, J.-P., Gosselin, C.: Nouvelle Architecture pour un Manipulateur Parallele a Six Degres de Liberte. Mech. Mach. Theory 26, 77–90 (1991)CrossRefGoogle Scholar
  8. 8.
    Yoshikawa, T.: Manipulability of Robotic Mechanisms. Int. J. Robot Res. 4, 3–9 (1985)CrossRefGoogle Scholar
  9. 9.
    Michalewicz, Z., Fogel, D.B.: How to solve it: modern heuristics. Springer, New York (2000)zbMATHGoogle Scholar
  10. 10.
    Deb, K.: Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Chichester (2001)zbMATHGoogle Scholar
  11. 11.
    Laumanns, M., Thiele, L., Deb, K., et al.: Archiving with Guaranteed Convergence and Diversity in Multi-Objective Optimization. In: Proc. of the Genetic and Evolutionary Comp. Conference, San Francisco, USA (2002)Google Scholar
  12. 12.
    Solteiro Pires, E.J., Mendes, L., de Moura Oliveira, P.B., et al.: Single-objective front optimization: application to RF circuit design. In: Proc. of the 10th annual conference on Genetic and evolutionary computation, Atlanta, USA (2008)Google Scholar
  13. 13.
    Gupta, M., Jin, L., Homma, N.: Static and Dynamic Neural Networks, From Fundamentals to Advanced Theory. John Wiley & Sons, Chichester (2003)CrossRefGoogle Scholar

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

Personalised recommendations