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Mathematical Problems in Engineering - Volume 2015 2015, Article ID 837540, 15 pages -

Research Article

Graduate School of Creative Science and Engineering, Waseda University, Tokyo 1698555, Japan

Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo 1698555, Japan

Graduate School of Informatics, Kyoto University, Kyoto 6068501, Japan

Received 7 March 2014; Revised 15 June 2014; Accepted 15 June 2014

Academic Editor: Yi Chen

Copyright © 2015 Kuniyuki Takahashi et al.
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We propose the new method of tool use with a tool-body assimilation model based on body babbling and a neurodynamical system for robots to use tools.
Almost all existing studies for robots to use tools require predetermined motions and tool features; the motion patterns are limited and the robots cannot use novel tools.
Other studies fully search for all available parameters for novel tools, but this leads to massive amounts of calculations.
To solve these problems, we took the following approach: we used a humanoid robot model to generate random motions based on human body babbling.
These rich motion experiences were used to train recurrent and deep neural networks for modeling a body image.
Tool features were self-organized in parametric bias, modulating the body image according to the tool in use.
Finally, we designed a neural network for the robot to generate motion only from the target image.
Experiments were conducted with multiple tools for manipulating a cylindrical target object.
The results show that the tool-body assimilation model is capable of motion generation.





Autor: Kuniyuki Takahashi, Tetsuya Ogata, Hadi Tjandra, Yuki Yamaguchi, and Shigeki Sugano

Fuente: https://www.hindawi.com/



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