Advertisement

Use of Genetic Algorithm for Robot-Posture

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 240)

Abstract

Robot-posture with genetic algorithm is presented in this paper. As a robot platform walking biped robot is used. To cope with the difficulties and explain unknown empirical laws in the robot, practical robot walking on a descending sloped floor is modeled by genetic architecture. These results from the modeling strategy is analyzed and compared.

Keywords

Genetic algorithm Robot posture Comparison analysis 

References

  1. 1.
    Vukobratovic M, Brovac B (2004) Zero-moment point-thirty five years of its life. Int J Humanoid Rob 1:157–173CrossRefGoogle Scholar
  2. 2.
    Vukobratovic M, Andric D, Borovac B (2005) Humanoid robot motion in unstructured environment-generation of various gait patterns from a single nominal. In: Kordic V, Lazinica A, Merdan M (eds) Cutting edge robotics. In Tech Google Scholar
  3. 3.
    Hirai K, Hirose M, Haikawa Y, Takenaka T (1998) The development of Honda humanoid robot. In: Proceedings of the IEEE international conference robotics and automation, pp 1321–1326Google Scholar
  4. 4.
    Vukobratovic M, Brovac B, Surla D, Stokic S (1990) Biped locomotion. Springer, New YorkCrossRefMATHGoogle Scholar
  5. 5.
    Kim D, Seo SJ, Park GT (2005) Zero-moment point trajectory modeling of a biped walking robot using an adaptive neuro-fuzzy systems. IET Control Theory Appl 152:411–426CrossRefGoogle Scholar
  6. 6.
    Kim D, Park GT (2007) Advanced humanoid robot based on the evolutionary inductive self-organizing network. Humanoid robots-new developments, pp 449–466 Google Scholar
  7. 7.
    Kim D, Park GT (2010) Intelligent walking modeling of humanoid robot using learning based neuro-fuzzy system. J Inst Control Rob Syst 16(10):963–968Google Scholar
  8. 8.
    Kim DW, Silva CW, Park GT (2010) Evolutionary design of Sugeno-type fuzzy systems for modeling humanoid robots. Int J Syst Sci 41(7):875–888CrossRefMATHGoogle Scholar
  9. 9.
    Chun BT, Cho MY, Jeong YS (2011) A study on environment construction for performance evaluation of face recognition for intelligent robot. J Korean Inst Inf Tech 9(11):81–87Google Scholar
  10. 10.
    Shin JH, Park JG (2012) Implementation of an articulated robot control system using an On/Off-line robot simulator with TCP/IP multiple networks. J Korean Inst Inf Tech 10(01):37–45Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht(Outside the USA) 2013

Authors and Affiliations

  1. 1.Department of Digital ElectronicsInha Technical CollegeIncheonSouth Korea
  2. 2.Deptartment of ElectronicsUniversity of IncheonIncheonSouth Korea

Personalised recommendations