Object dynamics prediction and motion generation based on reliable predictability

Shun Nishide, Tetsuya Ogata, Ryunosuke Yokoya, Jun Tani, Kazunori Komatani, Hiroshi G. Okuno

研究成果: Conference contribution

11 被引用数 (Scopus)

抄録

Consistency of object dynamics, which is related to reliable predictability, is an important factor for generating object manipulation motions. This paper proposes a technique to generate autonomous motions based on consistency of object dynamics. The technique resolves two issues: construction of an object dynamics prediction model and evaluation of consistency. The authors utilize Recurrent Neural Network with Parametric Bias to self-organize the dynamics, and link static images to the self-organized dynamics using a hierarchical neural network to deal with the first issue. For evaluation of consistency, the authors have set an evaluation function based on object dynamics relative to robot motor dynamics. Experiments have shown that the method is capable of predicting 90% of unknown object dynamics. Motion generation experiments have proved that the technique is capable of generating autonomous pushing motions that generate consistent rolling motions.

本文言語English
ホスト出版物のタイトル2008 IEEE International Conference on Robotics and Automation, ICRA 2008
ページ1608-1614
ページ数7
DOI
出版ステータスPublished - 2008 9 18
外部発表はい
イベント2008 IEEE International Conference on Robotics and Automation, ICRA 2008 - Pasadena, CA, United States
継続期間: 2008 5 192008 5 23

出版物シリーズ

名前Proceedings - IEEE International Conference on Robotics and Automation
ISSN(印刷版)1050-4729

Conference

Conference2008 IEEE International Conference on Robotics and Automation, ICRA 2008
国/地域United States
CityPasadena, CA
Period08/5/1908/5/23

ASJC Scopus subject areas

  • ソフトウェア
  • 制御およびシステム工学
  • 人工知能
  • 電子工学および電気工学

フィンガープリント

「Object dynamics prediction and motion generation based on reliable predictability」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル