Investigation of hybrid optimization methods to evolve effective gaits of a hexapedal robot

Yau Zen Chang*, Chin Yeh Peng, Yu Cheng Wu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

With the understanding that an efficient optimization method is crucial to evolve effective gaits of a walking robot, this work investigates several integrations of well known optimization techniques, including Taguchi method, particle swarm optimization algorithm, and Nelder-Mead simplex method. Four benchmark nonlinear optimization problems are chosen for performance comparison. Numerical results demonstrate the superiority of the Taguchi method that requires only limited number of trials to achieve minimization goals. The method is then implemented experimentally in the search of effective phase difference and cycle time of a six-legged walking robot.

Original languageEnglish
Title of host publicationProceedings - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010
Pages697-702
Number of pages6
DOIs
StatePublished - 2010
Event2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010 - Kitakyushu, Japan
Duration: 15 12 201017 12 2010

Publication series

NameProceedings - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010

Conference

Conference2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010
Country/TerritoryJapan
CityKitakyushu
Period15/12/1017/12/10

Keywords

  • Evolutionary robotics
  • Neider-mead simplex method
  • Particle swarm optimization
  • Taguchi method
  • Walking robot

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