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Joint Stiffness Tuning of Exoskeleton Robot H2 by Tacit Learning

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Symbiotic Interaction (Symbiotic 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9359))

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Abstract

Joint stiffness of the exoskeleton robot is one of the most important factors to support bipedal walking. In this paper, we discuss the robot joint stiffness tuning algorithm using the bio-mimetic learning method called tacit learning. We experimentally showed that the proposed controller can tune the joint stiffness of the exoskeleton robot by tuning the integral gain in the controller. The walking experiment wearing the exoskeleton robot suggest that the stiffness tuning is applicable to control the walking speed.

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References

  1. Scete, M., Doyle, J.: Bow ties, metabolism and disease. Trends Biotechnol. 22(9), 446–450 (2004)

    Article  Google Scholar 

  2. Alnajjar, F.S.K., Itkonen, M., Berenz, V., Tournier, M., Shimoda, S.: Sensor synergy as environmental input integration. Frontier in Neuroscience 15, article 436 (2015)

    Google Scholar 

  3. Shimoda, S., Kimura, H.: Bio-mimetic Approach to Tacit Learning based on Compound Control. IEEE Transactions on Systems, Man, and Cybernetics- Part B 40(1), 77–90 (2010)

    Article  Google Scholar 

  4. Shimoda, S., Yoshihara, Y., Kimura, H.: Adaptability of tacit learning in bipedal locomotion. IEEE Transactions on Autonomous Mental Development 5(2), 152–161 (2013)

    Article  Google Scholar 

  5. Iwatsuki, K., Oyama, S., Alnajjar, F.S., Shimoda, S., Yamamoto, M., Hirata, H.: Hand prosthesis equipped with a tacit learning system to auto-regulate forearm rotation. In: The 69th Annual Meeting of the American Society for Surgery of the Hand (2014)

    Google Scholar 

  6. Shimoda, S., Yoshihara, Y., Fujimoto, K., Yamamoto, T., Maeda, I., Kimura, H.: Stability analysis of tacit learning based on environmental signal accumulation. In: Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (2012)

    Google Scholar 

  7. Bortole, M., Venkatakrishnan, A., Zhu, F., Moreno, J.C., Francisco, G.E., Pons, J.L., Contreras-Vidal, J.L.: The H2 robotic exoskeleton for gait rehabilitation after stroke: early findings from a clinical study. Journal of NeuroEngineering and Rehabilitation (2015)

    Google Scholar 

  8. http://btcc.nagoya.riken.jp/biologic/biomot.html

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Author information

Authors and Affiliations

  1. RIKEN, Brain Science Institute, Wako, Japan

    Shingo Shimoda & Shotaro Okajima

  2. Brain-Machine Interface Systems Lab, Miguel Hernández University of Elche, Elche, Spain

    Álvaro Costa, Eduardo Ináẽz & Jose M. Azorín

  3. Neural Rehabilitation Group, the Spanish National Research Council, Madrid, Spain

    Guillermo Asin-Prieto, Jose L. Pons & Juan C. Moreno

  4. Nagoya University, Nagoya, Japan

    Shotaro Okajima & Yasuhisa Hasegawa

Authors
  1. Shingo Shimoda
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  2. Álvaro Costa
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  3. Guillermo Asin-Prieto
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  4. Shotaro Okajima
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  5. Eduardo Ináẽz
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  6. Yasuhisa Hasegawa
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  7. Jose M. Azorín
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  8. Jose L. Pons
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  9. Juan C. Moreno
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Corresponding author

Correspondence to Shingo Shimoda .

Editor information

Editors and Affiliations

  1. Sekr. MAR 4-3, Rm 4.041, TU Berlin, Berlin, Berlin

    Benjamin Blankertz

  2. Dept of Computer Science, University of Helsinki, Helsinki

    Giulio Jacucci

  3. Università di Padova, Padua

    Luciano Gamberini

  4. Università di Padova, Padua

    Anna Spagnolli

  5. Department of Psychology, Goldsmiths University, London

    Jonathan Freeman

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© 2015 Springer International Publishing Switzerland

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Cite this paper

Shimoda, S. et al. (2015). Joint Stiffness Tuning of Exoskeleton Robot H2 by Tacit Learning. In: Blankertz, B., Jacucci, G., Gamberini, L., Spagnolli, A., Freeman, J. (eds) Symbiotic Interaction. Symbiotic 2015. Lecture Notes in Computer Science(), vol 9359. Springer, Cham. https://doi.org/10.1007/978-3-319-24917-9_15

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  • DOI: https://doi.org/10.1007/978-3-319-24917-9_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24916-2

  • Online ISBN: 978-3-319-24917-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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