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Learning to Walk Fast: Optimized Hip Height Movement for Simulated and Real Humanoid Robots

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Abstract

The linear inverted pendulum model has been used predominantly to generate balanced humanoid walking. This model assumes that the hip height is fixed during the walk. In this paper, generating a fast walk is studied with the main focus on the effect of hip height movement. Our approach is based on modeling the hip height movement and learning its parameters in order to generate a fast walk. The hip height trajectory is generated using Fourier basis functions. The generated trajectory is the input to programmable Central Pattern Generators (CPGs) in order to modulate generated trajectories smoothly. The inverted pendulum model is utilized to model a balanced walking. A numerical approach is presented to control inverted pendulum dynamics. Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is employed to search for appropriate hip height trajectory and walking parameters that optimize walking speed. This approach has been tested not only to obtain fast forward walk but also a fast side walk. Experiments are conducted on both simulated and real NAO robots. The results show that the change from the learned forward walk to learned side walk is performed stably, which confirm the important role of using CPGs. The comparison of the results of the proposed gait model (and development approach) with those obtained using fixed hip height also shows that fixed height walking is slower than variable height walking.

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Authors and Affiliations

  1. DEI/FEUP - Department of Informatics Engineering, Faculty of Engineering of the University of Porto, Rua Dr. Roberto Frias s/n, 4200-465, Porto, Portugal

    Nima Shafii

  2. LIACC - Artificial Intelligence and Computer Science Laboratory, Rua Dr. Roberto Frias s/n, 4200-465, Porto, Portugal

    Nima Shafii & Luis Paulo Reis

  3. IEETA - Institute of Electronics and Telematics Engineering of Aveiro, Campus Universitário de Santiago, 3810-193, Aveiro, Portugal

    Nima Shafii & Nuno Lau

  4. Department of Electronics, Telecommunications and Informatics, University of Aveiro, 3810-193, Aveiro, Portugal

    Nuno Lau

  5. Department of Information System, School of Engineering, University of Minho, Campus de Azurem, 4800-058, Guimaraes, Portugal

    Luis Paulo Reis

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  1. Nima Shafii
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  2. Nuno Lau
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  3. Luis Paulo Reis
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Correspondence to Nima Shafii.

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Shafii, N., Lau, N. & Reis, L.P. Learning to Walk Fast: Optimized Hip Height Movement for Simulated and Real Humanoid Robots. J Intell Robot Syst 80, 555–571 (2015). https://doi.org/10.1007/s10846-015-0191-5

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  • DOI: https://doi.org/10.1007/s10846-015-0191-5

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