深層学習に基づくビジュアルサーボによる物体の位置決め

• 徳田 冬樹

  東北大学大学院工学研究科

• 荒井 翔悟

  東北大学大学院工学研究科

• 小菅 一弘

  東北大学大学院工学研究科

書誌事項

タイトル別名

• Object Positioning by Visual Servoing Based on Deep Learning
• シンソウ ガクシュウ ニ モトズク ビジュアルサーボ ニ ヨル ブッタイ ノ イチギメ

抄録

Visual servoing is capable of positioning robots based on images captured by cameras. To calculate the command value for robots, hand-designed image features and extraction of image features are required. Positioning accuracy is significantly influenced by the selection of the image features. In this study, we focus on the ability of convolutional neural networks (CNN) to extract features from images and output the angular velocity to control a manipulator. We propose a visual servoing technique based on CNN enabling the precise positioning of a texture less object grasped by a parallel gripper. The positioning can be achieved even the grasping position is different from the position when the target image was captured. The positioning accuracy of the proposed method is verified based on the positioning of an object into an alignment tray using a six-DOF manipulator. We confirmed that the proposed visual servoing technique can position an object precisely.

収録刊行物

• 計測自動制御学会論文集

  計測自動制御学会論文集 55 (11), 717-725, 2019

  公益社団法人 計測自動制御学会

キーワード

• visual servoing
• manipulator
• convolutional neural network

詳細情報

• CRID: 1390564227347948288
• NII論文ID: 130007748659
• NII書誌ID: AN00072392
• DOI: 10.9746/sicetr.55.717
• ISSN: 18838189
• ISSN: 04534654
• NDL書誌ID: 030094751
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I030094751
• Web Site: https://www.jstage.jst.go.jp/article/sicetr/55/11/55_717/_pdf
• 本文言語コード: ja
• データソース種別:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可