The Abstracts of the international conference on advanced mechatronics : toward evolutionary fusion of IT and mechatronics : ICAM
Online ISSN : 2424-3116
2015.6
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Feature Extraction by Deep Learning for Improved In-Hand Manipulation
Satoshi FUNABASHITakashi SATOAlexander SCHMITZShigeki SUGANO
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CONFERENCE PROCEEDINGS FREE ACCESS

Pages 31-32

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Abstract
This article presents feature extraction with deep learning for in-hand manipulation. It is important that robot hands can manipulate different sized and shaped objects. In order to generate versatile manipulation with such objects, we used deep learning to extract critical information from object manipulating motions.
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© 2015 The Japan Society of Mechanical Engineers
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