Artificial Life and Robotics

, Volume 19, Issue 2, pp 193–200 | Cite as

Estimation of physical interaction between a musculoskeletal robot and its surroundings

  • Kenji Urai
  • Yuya Okadome
  • Yoshihiro Nakata
  • Yutaka Nakamura
  • Hiroshi Ishiguro
Original Article


Recently, robots are expected to support our daily lives in real environments. In such environments, however, there are a lot of obstacles and the motion of the robot is affected by them. In this research, we develop a musculoskeletal robotic arm and a system identification method for coping with external forces while learning the dynamics of complicated situations, based on Gaussian process regression (GPR). The musculoskeletal robot has the ability to cope with external forces by utilizing a bio-inspired mechanism. GPR is an easy-to-implement method, but can handle complicated prediction tasks. The experimental results show that the behavior of the robot while interacting with its surroundings can be predicted by our method.


Musculoskeletal robot Gaussian process regression Locality-sensitive hashing 



This work was supported in part by JSPS KAKENHI Grant-in-Aid for Young Scientists (A) No.80720664.


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Copyright information

© ISAROB 2014

Authors and Affiliations

  • Kenji Urai
    • 1
  • Yuya Okadome
    • 1
  • Yoshihiro Nakata
    • 1
  • Yutaka Nakamura
    • 1
  • Hiroshi Ishiguro
    • 1
  1. 1.Osaka UniversityOsakaJapan

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