A Comparative Study between Genetic Algorithm and Genetic Programming Based Gait Generation Methods for Quadruped Robots

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{conf/evoW/SeoH10,

• title = "A Comparative Study between Genetic Algorithm and Genetic Programming Based Gait Generation Methods for Quadruped Robots",
• author = "Kisung Seo and Soohwan Hyun",
• year = "2010",
• booktitle = "EvoApplications 2010",
• editor = "Cecilia {Di Chio} and Stefano Cagnoni and Carlos Cotta and Marc Ebner and Aniko Ekart and Anna I. Esparcia-Alcazar and Chi-Keong Goh and Juan J. Merelo and Ferrante Neri and Mike Preuss and Julian Togelius and Georgios N. Yannakakis",
• volume = "6024",
• series = "Lecture Notes in Computer Science",
• pages = "352--360",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1007/978-3-642-12239-2_37",
• bibdate = "2010-04-12",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/evoW/evoappl2010-1.html#SeoH10",
• abstract = "Planning gaits for legged robots is a challenging task that requires optimising parameters in a highly irregular and multidimensional space. Two gait generation methods using GA (Genetic Algorithm), GP (genetic programming) are compared to develop fast locomotion for a quadruped robot. GA-based approaches seek to optimize a pre-selected set of parameters which include locus of paw and stance parameters of initial position. A GP-based technique is an effective way to generate a few joint trajectories instead of the locus of paw positions and many stance parameters. Optimisations for two proposed methods are executed and analysed using a Webots simulation of the quadruped robot built by Bioloid. Furthermore, simulation results for the two proposed methods are tested in a real quadruped robot, and the performance and motion features of GA-, GP -based methods are compared.",
• affiliation = "Seokyeong University Dept. of Electronic Engineering Seoul Korea",

}

Genetic Programming entries for Kisung Seo Soohwan Hyun

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