Skip to main content
SpringerLink
Log in
Book cover

European Conference on the Applications of Evolutionary Computation

EvoApplications 2013: Applications of Evolutionary Computation pp 599–605Cite as

Toward Automatic Gait Generation for Quadruped Robots Using Cartesian Genetic Programming

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7835))

Abstract

This paper introduces a new gait generation method for quadruped robots using CGP (Cartesian Genetic Programming) based on refinement of regression polynomials for a joint trajectory. CGP uses as genotype a linear string of integers that are mapped to a directed graph. Therefore, some evolved modules for regression polynomials in CGP can be shared and reused among multiple outputs for joint trajectories. To investigate the effectiveness of the proposed approach, experiments on gaits were executed for a Bioloid quadruped robot in the Webots environment.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Akın, H.L., Meriçli, Ç., Meriçli, T., Kaplan, K., Çelik, B.: Cerberus’05 Team Report, Technical Report, Boğaziçi University (2005)

    Google Scholar 

  2. Chen, W.: Odometry Calibration and Gait Optimisation. Technical Report. The University of New South Wales, School of Computer Science and Engineering (2005)

    Google Scholar 

  3. Doan, P., Vo, H., Kim, H., Kim, S.: A New Approach for Development of Quadruped Robot Based on Biological Concepts. International Journal of Precision Engineering and Manufacturing 11, 559–568 (2010)

    Article  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(IROS 2006), pp. 5756–5761. IEEE Press, China (2006)

    Chapter  Google Scholar 

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

    Article  Google Scholar 

  6. Hornby, G.S., Takamura, S., Yamamoto, T., Fujita, M.: Autonomous evolution of dynamic gaits with two quadruped robots. IEEE Trans. Robotics 21, 402–410 (2005)

    Article  Google Scholar 

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

    MATH  Google Scholar 

  8. Koza, J.R.: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge (1994)

    MATH  Google Scholar 

  9. Miller, J.F., Thomson, P.: Cartesian Genetic Programming. In: Poli, R., Banzhaf, W., Langdon, W.B., Miller, J., Nordin, P., Fogarty, T.C. (eds.) EuroGP 2000. LNCS, vol. 1802, pp. 121–132. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  10. Miller, J.F., Job, D., Vassilev, V.K.: Principles in the Evolutionary Design of Digital Circuits - Part I. Genetic Programming and Evolvable Machines 1, 8–35 (2000)

    Google Scholar 

  11. Raibert, M., Blankespoor, K., Nelson, G., Playter, R.: Bigdog, the rough-terrain quadruped robot. Technical report, Boston Dynamics (2008)

    Google Scholar 

  12. Seo, K., Hyun, S.: A Comparative Study between Genetic Algorithm and Genetic Programming Based Gait Generation Methods for Quadruped Robots. In: Di Chio, C., Cagnoni, S., Cotta, C., Ebner, M., Ekárt, A., Esparcia-Alcazar, A.I., Goh, C.-K., Merelo, J.J., Neri, F., Preuß, M., Togelius, J., Yannakakis, G.N. (eds.) EvoApplicatons 2010, Part I. LNCS, vol. 6024, pp. 352–360. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  13. Seo, K., Hyun, S., Goodman, E.: Genetic Programming-Based Automatic Gait Generation in Joint Space for a Quadruped Robot. Advanced Robotics 24, 2199–2214 (2010)

    Article  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. Yosinski, J., Clune, J., Hidalgo, D., Nguyen, S., Zagal, C.J., Lipson, H.: Evolving Robot Gaits in Hardware: the HyperNEAT Generative Encoding Vs. Parameter Optimization, Advances in Artificial Life. In: Proceedings of the 11th European Conference on the Synthesis and Simulation of Living Systems, pp. 890–897 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

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

    Kisung Seo

  2. Hyundai Heavy Industries Research Institute, Yongin, Korea

    Soohwan Hyun

Authors
  1. Kisung Seo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Soohwan Hyun
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. S2 Grupo, C/ Ramiro de Maeztu 7, 46022, Valencia, Spain

    Anna I. Esparcia-Alcázar

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Seo, K., Hyun, S. (2013). Toward Automatic Gait Generation for Quadruped Robots Using Cartesian Genetic Programming. In: Esparcia-Alcázar, A.I. (eds) Applications of Evolutionary Computation. EvoApplications 2013. Lecture Notes in Computer Science, vol 7835. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37192-9_60

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37192-9_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37191-2

  • Online ISBN: 978-3-642-37192-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation