書誌事項
- タイトル別名
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- Visual servo based on CAD model using machine learning
説明
<p>Image Based Visual Servo(IBVS) is known as a controlled method using data from vision sensors, which is to place the object into a specified place with a desired orientation. In order to place an object, the derivation of a matrix called image jacobian is necessary. The image jacobian can be used only for the image captured in the vicinity of the target image. There for, the rederivation of image jacobian is necessary when placing an object into different target places which takes time and efforts. In this paper, we propose a new visual servo based on deep learning and evaluate it in a simulation. By including various goal images in the data set, we achieved placing an object into different targets using a single trained convolutional neural network. Details of the data set and the architecture of convolutional neural network is described in this paper.</p>
収録刊行物
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- ロボティクス・メカトロニクス講演会講演概要集
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ロボティクス・メカトロニクス講演会講演概要集 2018 (0), 2A2-J15-, 2018
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390564238056186752
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- NII論文ID
- 130007551811
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- ISSN
- 24243124
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
- OpenAIRE
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- 抄録ライセンスフラグ
- 使用不可