Extracting multi-modal dynamics of objects using RNNPB

Tetsuya Ogata, Hayato Ohba, Jun Tani, Kazunori Komatani, Hiroshi G. Okuno

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

16 Citations (Scopus)

Abstract

Dynamic features play an important role in recognizing objects that have similar static features in colors and or shapes. This paper focuses on active sensing that exploits dynamic feature of an object. An extended version of the robot, Robovie-IIs, moves an object by its arm to obtain its dynamic features. Its issue is how to extract symbols from various kinds of temporal states of the object. We use the recurrent neural network with parametric bias (RNNPB) that generates selforganized nodes in the parametric bias space. The RNNPB with 42 neurons was trained with the data of sounds, trajectories, and tactile sensors generated while the robot was moving/hitting an object with its own arm. The clusters of 20 kinds of objects were successfully self-organized. The experiments with unknown (not trained) objects demonstrated that our method configured them in the PB space appropriately, which proves its generalization capability.

Original languageEnglish
Title of host publication2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
Pages160-165
Number of pages6
DOIs
Publication statusPublished - 2005 Dec 1
Externally publishedYes
EventIEEE IRS/RSJ International Conference on Intelligent Robots and Systems, IROS 2005 - Edmonton, AB, Canada
Duration: 2005 Aug 22005 Aug 6

Publication series

Name2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS

Conference

ConferenceIEEE IRS/RSJ International Conference on Intelligent Robots and Systems, IROS 2005
CountryCanada
CityEdmonton, AB
Period05/8/205/8/6

Keywords

  • Active sensing
  • Humanoid robot
  • Recurrent neural network

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Control and Systems Engineering

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  • Cite this

    Ogata, T., Ohba, H., Tani, J., Komatani, K., & Okuno, H. G. (2005). Extracting multi-modal dynamics of objects using RNNPB. In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS (pp. 160-165). [1544975] (2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS). https://doi.org/10.1109/IROS.2005.1544975