Learning the reachable space of a humanoid robot: A bio-inspired approach

Lorenzo Jamone, Lorenzo Natale, Kenji Hashimoto, Giulio Sandini, Atsuo Takanishi

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

In this paper we describe how a humanoid robot can learn a representation of its own reachable space from motor experience: a Reachable Space Map. The map provides information about the reachability of a visually detected object (i.e. a 3D point in space). We propose a bio-inspired solution in which the map is built in a gaze-centered reference frame: the position of a point in space is encoded with the motor configuration of the robot head and eyes which allows the fixation of that point. We provide experimental results in which a simulated humanoid robot learns this map autonomously and we discuss how the map can be used for planning whole-body and bimanual reaching.

本文言語English
ホスト出版物のタイトル2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2012
ページ1148-1154
ページ数7
DOI
出版ステータスPublished - 2012 10 18
イベント2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2012 - Rome, Italy
継続期間: 2012 6 242012 6 27

出版物シリーズ

名前Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
ISSN(印刷版)2155-1774

Conference

Conference2012 4th IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2012
CountryItaly
CityRome
Period12/6/2412/6/27

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biomedical Engineering
  • Mechanical Engineering

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