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

  • Kisung Seo
  • Soohwan Hyun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6024)


Planning gaits for legged robots is a challenging task that requires optimizing 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. Optimizations for two proposed methods are executed and analyzed 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.


Robot Automatic Gait Generation Quadruped Robot Genetic Algorithm Joint Space Trajectory Genetic Programming 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Kisung Seo
    • 1
  • Soohwan Hyun
    • 1
  1. 1.Dept. of Electronic EngineeringSeokyeong UniversitySeoulKorea

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