Tool-body assimilation model using a neuro-dynamical system for acquiring representation of tool function and motion

Kuniyuki Takahshi, Tetsuya Ogata, Hadi Tjandra, Yuki Yamaguchi, Yuki Suga, Shigeki Sugano

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

3 Citations (Scopus)

Abstract

In this paper, we propose a tool-body assimilation model that implements a multiple time-scales recurrent neural network (MTRNN). Our model allows a robot to acquire the representation of a tool function and the required motion without having any prior knowledge of the tool. It is composed of five modules: image feature extraction, body model, tool dynamics feature, tool recognition, and motion recognition. Self-organizing maps (SOM) are used for image feature extraction from raw images. The MTRNN is used for body model learning. Parametric bias (PB) nodes are used to learn tool dynamic features. The PB nodes are attached to the neurons of the MTRNN to modulate the body model. A hierarchical neural network (HNN) is implemented for tool and motion recognition. Experiments were conducted using OpenHRP3, a robotics simulator, with multiple tools. The results show that the tool-body assimilation model is capable of recognizing tools, including those having an unlearned shape, and acquires the required motions accordingly.

Original languageEnglish
Title of host publicationAIM 2014 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1255-1260
Number of pages6
ISBN (Print)9781479957361
DOIs
Publication statusPublished - 2014 Jan 1
Event2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2014 - Besancon, France
Duration: 2014 Jul 82014 Jul 11

Publication series

NameIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM

Conference

Conference2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2014
CountryFrance
CityBesancon
Period14/7/814/7/11

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Science Applications
  • Electrical and Electronic Engineering

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    Takahshi, K., Ogata, T., Tjandra, H., Yamaguchi, Y., Suga, Y., & Sugano, S. (2014). Tool-body assimilation model using a neuro-dynamical system for acquiring representation of tool function and motion. In AIM 2014 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics (pp. 1255-1260). [6878254] (IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AIM.2014.6878254