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Evolutionary Multi-Objective Optimization for Biped Walking

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Book cover Simulated Evolution and Learning (SEAL 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5361))

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Abstract

We introduce an application of Evolutionary Multi- Objective Optimization on multi-layered robot control system. Recent robot control systems consist of many simple function modules. The parameter settings for most of these modules were manually adjusted in previous research. Our goal is to develop an automatic parameter adjustment method for the robot control system. In this paper, we focused on three modules as the experiment environment: whole-body motion generator, footstep planner and path planner. At first the features of these three modules are examined. Then we discuss the trade-off relationship between the requirements of each module. Finally, we examined an application of Evolutionary Multi-Objective Optimization on this problem.

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References

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Author information

Authors and Affiliations

  1. Graduate School of Frontier Sciences, The University of Tokyo, Japan

    Toshihiko Yanase & Hitoshi Iba

Authors
  1. Toshihiko Yanase
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  2. Hitoshi Iba
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Editor information

Editors and Affiliations

  1. School of Computer Science and information Technology, RMIT University, VIC 3001, Melbourne, Australia

    Xiaodong Li

  2. Melbourne School Engineering, Department of Computer Science and Software Engineering, The University of Melbourne, VIC 3001, Melbourne, Australia

    Michael Kirley

  3. School of Mathematics, Statistics and Computer Science, Victoria University of Wellington, P.O. Box 600, 6140, Wellington, New Zealand

    Mengjie Zhang

  4. Faculty of Information Technology, Monash University, Clayton Campus, VIC 3800, Australia

    David Green

  5. School of Computer Science and Information Technology, RMIT University, VIC 3001, Melbourne, Australia

    Vic Ciesielski

  6. School of Information Technology and Electrical Engineering, Australian Defence Force Academy, University of New South Wales, Canberra, Australia

    Hussein Abbass

  7. School of Computer Science, University of Adelaide, SA 5005, Adelaide, Australia

    Zbigniew Michalewicz

  8. Faculty of Information and Communication Technologies, Swinburne University of Technology, Melbourne, Australia

    Tim Hendtlass

  9. Indian Institute of Technology Kanpur, Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory (KanGAL), 208016, Kanpur, Uttar Pradesh, India

    Kalyanmoy Deb

  10. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576, Singapore

    Kay Chen Tan

  11. Institute AIFB, University of Karlsruhe, 76128, Karlsruhe, Germany

    Jürgen Branke

  12. Xi’an Jiaotong-Liverpool University, 215123, Suzhoum, China

    Yuhui Shi

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© 2008 Springer-Verlag Berlin Heidelberg

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Cite this paper

Yanase, T., Iba, H. (2008). Evolutionary Multi-Objective Optimization for Biped Walking. In: Li, X., et al. Simulated Evolution and Learning. SEAL 2008. Lecture Notes in Computer Science, vol 5361. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89694-4_64

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  • DOI: https://doi.org/10.1007/978-3-540-89694-4_64

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89693-7

  • Online ISBN: 978-3-540-89694-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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