Genetic Programming-Based Automatic Gait Generation in Joint Space for a Quadruped Robot
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @Article{Seo:2010:AR,
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title = "Genetic Programming-Based Automatic Gait Generation in
Joint Space for a Quadruped Robot",
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author = "Kisung Seo and Soohwan Hyun and Erik D. Goodman",
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journal = "Advanced Robotics",
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year = "2010",
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number = "15",
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volume = "24",
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pages = "2199--2214",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "0169-1864",
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DOI = "doi:10.1163/016918610X534312",
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bibdate = "2010-12-19",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/journals/ar/ar24.html#SeoHG10",
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abstract = "This paper introduces a new approach to developing a
fast gait for a quadruped robot using genetic
programming (GP). Planning gaits for legged robots is a
challenging task that requires optimising parameters in
a highly irregular and multi-dimensional space. Several
recent approaches have focused on using genetic
algorithms (GAs) to generate gaits automatically and
have shown significant improvement over previous gait
optimization results. Most current GA-based approaches
optimise only a small, pre-selected set of parameters,
but it is difficult to decide which parameters should
be included in the optimisation to get the best
results. Moreover, the number of pre-selected
parameters is at least 10, so it can be relatively
difficult to optimise them, given their high degree of
interdependence. To overcome these problems of the
typical GA-based approach, we have proposed a seemingly
more efficient approach that optimises joint
trajectories instead of locus-related parameters in
Cartesian space, using GP. Our GP-based method has
obtained much-improved results over the GA-based
approaches tested in experiments on the Sony AIBO ERS-7
in the Webots environment. The elite archive mechanism
is introduced to combat the premature convergence
problems in GP and has shown better results than a
traditional multi-population approach.",
- }
Genetic Programming entries for
Kisung Seo
Soohwan Hyun
Erik Goodman
Citations