An Extended Mobile Manipulation Robot Learning Novel Objects

• Nakamura Tomoaki

  UEC Tokyo

• Attamimi Muhammad

  UEC Tokyo

• Sugiura Komei

  NICT

• Nagai Takayuki

  UEC Tokyo

• Iwahashi Naoto

  NICT

• Toda Tomoki

  Nara Institute of Science and Technology

• Okada Hiroyuki

  Tamagawa University

• Omori Takashi

  Tamagawa University

Bibliographic Information

Other Title

• 拡張モバイルマニピュレーションのための新規物体の学習
• カクチョウ モバイルマニピュレーション ノ タメ ノ シンキ ブッタイ ノ ガクシュウ

Abstract

It is convenient for users to teach novel objects to a domestic service robot with a simple procedure. In this paper, we propose a method for learning the images and names of these objects shown by the users. The object images are segmented out from cluttered scenes by using motion attention. Phoneme recognition and voice conversion are used for the speech recognition and synthesis of the object names that are out of vocabulary. In the experiments conducted with 120 everyday objects, we have obtained an accuracy of 91% for object recognition and an accuracy of 82% for word recognition. Furthermore, we have implemented the proposed method on a physical robot, DiGORO, and evaluated its performance by using RoboCup@Home's “Supermarket” task. The results have shown that DiGORO has outperformed the highest score obtained in the RoboCup@Home 2009 competition.

Journal

• Journal of the Robotics Society of Japan

  Journal of the Robotics Society of Japan 30 (2), 213-224, 2012

  The Robotics Society of Japan

Keywords

• Mobile Manipulation
• Object Learning
• Object Recognition
• Out-of-vocabulary
• RoboCup@Home

Details

• CRID: 1390282679704379392
• NII Article ID: 10030209234
• NII Book ID: AN00141189
• DOI: 10.7210/jrsj.30.213
• ISSN: 18847145
• ISSN: 02891824
• NDL BIB ID: 023599282
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I023599282
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed