Tool-Body Assimilation Model Based on Body Babbling and a Neuro-Dynamical System for Motion Generation

  • Kuniyuki Takahashi
  • Tetsuya Ogata
  • Hadi Tjandra
  • Shingo Murata
  • Hiroaki Arie
  • Shigeki Sugano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8681)

Abstract

We propose a model for robots to use tools without predetermined parameters based on a human cognitive model. Almost all existing studies of robot using tool require predetermined motions and tool features, so the motion patterns are limited and the robots cannot use new tools. Other studies use a full search for new tools; however, this entails an enormous number of calculations. We built a model for tool use based on the phenomenon of tool-body assimilation using the following approach: We used a humanoid robot model to generate random motion, based on human body babbling. These rich motion experiences were then used to train a recurrent neural network for modeling a body image. Tool features were self-organized in the parametric bias modulating the body image according to the used tool. Finally, we designed the neural network for the robot to generate motion only from the target image.

Keywords

tool-body assimilation multiple time-scales recurrent neural network 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Kuniyuki Takahashi
    • 1
  • Tetsuya Ogata
    • 2
  • Hadi Tjandra
    • 1
  • Shingo Murata
    • 1
  • Hiroaki Arie
    • 2
  • Shigeki Sugano
    • 1
  1. 1.School of Creative Science and EngineeringWaseda UniversityTokyoJapan
  2. 2.School of Fundamental Science and EngineeringWaseda UniversityTokyoJapan

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