Interactive online learning of the kinematic workspace of a humanoid robot

Lorenzo Jamone*, Lorenzo Natale, Giulio Sandini, Atsuo Takanishi

*この研究の対応する著者

研究成果: Conference contribution

12 被引用数 (Scopus)

抄録

We describe an interactive learning strategy that enables a humanoid robot to build a representation of its workspace: we call it a Reachable Space Map. The robot learns this map autonomously and online during the execution of goal-directed reaching movements; reaching control is based on kinematic models that are learned online as well. The map can be used to estimate the reachability of a fixated object and to plan preparatory movements (e.g. bending or rotating the waist) that improve the effectiveness of the subsequent reaching action. Three main concepts make our solution innovative with respect to previous works: the use of a gaze-centered motor representation to describe the robot workspace, the primary role of action in building and representing knowledge (i.e. interactive learning), the realization of autonomous online learning. We evaluate our strategy by learning the workspace of a simulated humanoid robot and we show how this knowledge can be exploited to plan and execute complex actions, like whole-body bimanual reaching.

本文言語English
ホスト出版物のタイトル2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012
ページ2606-2612
ページ数7
DOI
出版ステータスPublished - 2012 12月 1
イベント25th IEEE/RSJ International Conference on Robotics and Intelligent Systems, IROS 2012 - Vilamoura, Algarve, Portugal
継続期間: 2012 10月 72012 10月 12

出版物シリーズ

名前IEEE International Conference on Intelligent Robots and Systems
ISSN(印刷版)2153-0858
ISSN(電子版)2153-0866

Conference

Conference25th IEEE/RSJ International Conference on Robotics and Intelligent Systems, IROS 2012
国/地域Portugal
CityVilamoura, Algarve
Period12/10/712/10/12

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ソフトウェア
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ サイエンスの応用

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