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Gait Planning of Biped Robots Using Soft Computing: An Attempt to Incorporate Intelligence

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Intelligent Autonomous Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 275))

Abstract

This chapter deals with the issues related to incorporation of intelligence using soft computing to biped robots moving on some uneven terrains, such as staircases, sloping surfaces, ditches, and others. The said problems have been solved utilizing both analytical as well as soft computing-based approaches. In the analytical approach, the concepts of inverse kinematics and static balance have been used to generate the gaits of lower limbs and trunk, respectively, and its dynamic balance has been verified utilizing the position of zero moment point, whereas in soft computing-based approaches, either neural network- or fuzzy logic-based gait planner has been used to generate the motion of trunk and swing foot of the biped robot. The knowledge bases of neural network and fuzzy logic-based approaches have been optimized separately using a genetic algorithm off-line. The performances of the developed approaches have been tested through computer simulations.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, DVR & Dr. HS MIC College of Technology, Kanchikacherla, 521180, India

    Pandu Ranga Vundavilli

  2. Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur, 721302, India

    Dilip Kumar Pratihar

Authors
  1. Pandu Ranga Vundavilli
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  2. Dilip Kumar Pratihar
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Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur, India

    Dilip Kumar Pratihar

  2. School of Electrical and Information Engineering, University of South Australia, Mawson Lakes Campus, Adelaide, South Australia, Australia

    Lakhmi C. Jain

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© 2010 Springer-Verlag Berlin Heidelberg

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Vundavilli, P.R., Pratihar, D.K. (2010). Gait Planning of Biped Robots Using Soft Computing: An Attempt to Incorporate Intelligence. In: Pratihar, D.K., Jain, L.C. (eds) Intelligent Autonomous Systems. Studies in Computational Intelligence, vol 275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11676-6_4

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  • DOI: https://doi.org/10.1007/978-3-642-11676-6_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11675-9

  • Online ISBN: 978-3-642-11676-6

  • eBook Packages: EngineeringEngineering (R0)

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