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

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Applications of Evolutionary Computation (EvoApplications 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6024))

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Abstract

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.

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References

  1. Bekey, G.A.: Autonomous Robots-From Biological Inspiration to Implementation and Control. MIT Press, Cambridge (2005)

    Google Scholar 

  2. Busch, J., Ziegler, J., Aue, C., Ross, A., Sawitzki, D., Banzhaf, W.: Automatic generation of control programs for walking robots using genetic programming. In: Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A.G.B. (eds.) EuroGP 2002. LNCS, vol. 2278, pp. 258–267. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  3. Chernova, S., Veloso, M.: An Evolutionary Approach To Gait Learning For Four-Legged Robots. In: Proceedings of IROS 2004, Sendai, Japan, September 2004, pp. 2562–2567 (2004)

    Google Scholar 

  4. Dong, H., Zhao, M., Zhang, J., Shi, Z., Zhang, N.: Gait Planning Of Quadruped Robot Based On Third-Order Spline Interpolation. In: Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China, October 9-15, pp. 5756–5761 (2006)

    Google Scholar 

  5. Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading (1989)

    MATH  Google Scholar 

  6. Golubovic, D., Hu, H.: Parameter Optimisation of an Evolutionary Algorithm for On-line Gait Generation of Quadruped Robots. In: Proceedings of IEEE International Conference on Industrial Technology – ICIT 2003, Maribor, Slovenia, December 2003, pp. 221–226 (2003)

    Google Scholar 

  7. Hornby, G.S., Takamura, S., Yamamoto, T., Fujita, M.: Autonomous Evolution of Dynamic Gaits with Two Quadruped Robots. IEEE Trans. Robotics 21(3), 402–410 (2005)

    Article  Google Scholar 

  8. Hohl, L., Tellez, R., Michel, O., Ijspeert, A.J.: Aibo and Webots: Simulation, wireless remote control and controller transfer. Robotics and Autonomous Systems 54(6), 472–485 (2006)

    Article  Google Scholar 

  9. Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)

    MATH  Google Scholar 

  10. Mericli, T., Akın, H.L., Mericli, C., Kaplan, K., Celik, B.: The Cerbus 2005 Team Report

    Google Scholar 

  11. Robotis Corporation, http://www.robotis.com

  12. Röfer, T.: Evolutionary Gait-Optimization Using a Fitness Function Based on Proprioception. In: Nardi, D., Riedmiller, M., Sammut, C., Santos-Victor, J. (eds.) RoboCup 2004. LNCS (LNAI), vol. 3276, pp. 310–322. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  13. Seo, K., Hyun, S.: Genetic Programming Based Automatic Gait Generation for Quadruped Robots. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2008, Atlanta, July 2008, pp. 293–294 (2008)

    Google Scholar 

  14. Tenreiro, J.A., Silva, M.F.: An Overview of Legged Robots. In: Proceedings of the International Symposium on Mathematical Methods in Engineering, pp. 27–29 (2006)

    Google Scholar 

  15. Wang, Z.D., Wong, J., Tam, T., Leung, B., Kim, M.S., Brooks, J., Chang, A., Huben, N.V.: The 2002 rUNSWift Team Report (2002)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Electronic Engineering, Seokyeong University, Seoul, Korea

    Kisung Seo & Soohwan Hyun

Authors
  1. Kisung Seo
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  2. Soohwan Hyun
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, University of Strathclyde, 16 Richmond Street, G1 1XQ, Glasgow, UK

    Cecilia Di Chio

  2. Department of Computer Engineering, University of Parma, Viale Usberti 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  3. Departmento Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Campus Teatinos, 29071, Málaga, Spain

    Carlos Cotta

  4. Wilhelm Schickard-Institut für Informatik, Sand 1, Universität Tübingen, 72076, Tübingen, Germany

    Marc Ebner

  5. Computer Science, Aston Triangle, Aston University, B4 7ET, Birmingham, UK

    Anikó Ekárt

  6. Instituto Tecnológico de Informática, Universidad Politécnica de Valencia, Edif. 8G Acceso B, 46022, Valencia, Spain

    Anna I. Esparcia-Alcazar

  7. Advanced Technology Centre Rolls-Royce, Singapore, Singapore

    Chi-Keong Goh

  8. Departamento de Electrónica y Tnologia de los Computadores, University of Granada, 18071, Grenada, Spain

    Juan J. Merelo

  9. Department of Mathematical Information Technology,, University of Jyväskylä, 4th Floor, P.O. Box 25, 40014, Agora, Finland

    Ferrante Neri

  10. Lehrstuhl für Algorithm Engineering, TU Dortmund, Otto-Hahn-Straße 14, 44227, Dortmund, Germany

    Mike Preuß

  11. Center for Computer Games Research, IT University of Copenhagen, Rued Langgaards Vej 7, 2300, Copenhagen S, Denmark

    Julian Togelius  & Georgios N. Yannakakis  & 

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Seo, K., Hyun, S. (2010). A Comparative Study between Genetic Algorithm and Genetic Programming Based Gait Generation Methods for Quadruped Robots. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2010. Lecture Notes in Computer Science, vol 6024. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12239-2_37

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  • DOI: https://doi.org/10.1007/978-3-642-12239-2_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12238-5

  • Online ISBN: 978-3-642-12239-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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