Hopping robot using pelvic movement and leg elasticity

Takuya Otani, Kazuhiro Uryu, Masaaki Yahara, Akihiro Iizuka, Shinya Hamamoto, Shunsuke Miyamae, Kenji Hashimoto, Matthieu Destephe, Masanori Sakaguchi, Yasuo Kawakami, Hun Ok Lim, Atsuo Takanishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Analysis of human running has revealed that the motion of the human leg can be modeled by a compression spring because leg’s joints behave like a torsion spring. In addition, the pelvic movement in the frontal plane contributes to the increase in jumping force. We therefore assumed that human-like running, which requires higher output power than that of existing humanoid robots, could be realized based on these characteristics. Hence, we developed a model composed of a body mass, a pelvis and a rotational joint leg, and fabricated the leg by incorporating a stiffness adjustment mechanism that uses two leaf springs. In this way, we were able to achieve a human-like joint stiffness, which could be adjusted by varying the effective length of one of the leaf springs. We achieved hopping by resonance of the pelvic movement and joints’ elasticity.

Original languageEnglish
Title of host publicationMechanisms and Machine Science
PublisherKluwer Academic Publishers
Number of pages9
ISBN (Print)9783319070575
Publication statusPublished - 2014
Event20th CISM-IFToMM Symposium on Theory and Practice of Robots and Manipulators, ROMANSY 2014 - Moscow, Russian Federation
Duration: 2014 Jun 232014 Jun 26


Other20th CISM-IFToMM Symposium on Theory and Practice of Robots and Manipulators, ROMANSY 2014
CountryRussian Federation


  • Hopping
  • Human motion analysis
  • Humanoid

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering

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    Otani, T., Uryu, K., Yahara, M., Iizuka, A., Hamamoto, S., Miyamae, S., Hashimoto, K., Destephe, M., Sakaguchi, M., Kawakami, Y., Lim, H. O., & Takanishi, A. (2014). Hopping robot using pelvic movement and leg elasticity. In Mechanisms and Machine Science (Vol. 22, pp. 235-243). Kluwer Academic Publishers. https://doi.org/10.1007/978-3-319-07058-2_27