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Autonomous manipulation with a general-purpose simple hand.

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Title: Autonomous manipulation with a general-purpose simple hand.
Authors: Mason, Matthew T1, Rodriguez, Alberto1, Srinivasa, Siddhartha S1, Vazquez, Andrés S2
Source: International Journal of Robotics Research. May2012, Vol. 31 Issue 5, p688-703. 16p.
Subjects: Robotics, Table manipulation (Computer science), Machine theory, Prototypes, Localization theory, Object recognition (Computer vision), Computer vision
Abstract: While complex hands seem to offer generality, simple hands are often more practical. This raises the question: how do generality and simplicity trade off in the design of robot hands? This paper explores the tension between simplicity in hand design and generality in hand function. It raises arguments both for and against simple hands, it considers several familiar examples, and it proposes an approach for autonomous manipulation using a general-purpose but simple hand. We explore the approach in the context of a bin-picking task, focused on grasping, recognition, and localization. The central idea is to use learned knowledge of stable grasp poses as a cue for object recognition and localization. This leads to some novel design criteria, such as minimizing the number of stable grasp poses. Finally, we describe experiments with two prototype hands to perform bin-picking of highlighter markers. [ABSTRACT FROM PUBLISHER]
Copyright of International Journal of Robotics Research is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 74435975
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PubType: Academic Journal
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IllustrationInfo
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Robotics+Research%22">International Journal of Robotics Research</searchLink>. May2012, Vol. 31 Issue 5, p688-703. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Robotics%22">Robotics</searchLink><br /><searchLink fieldCode="DE" term="%22Table+manipulation+%28Computer+science%29%22">Table manipulation (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+theory%22">Machine theory</searchLink><br /><searchLink fieldCode="DE" term="%22Prototypes%22">Prototypes</searchLink><br /><searchLink fieldCode="DE" term="%22Localization+theory%22">Localization theory</searchLink><br /><searchLink fieldCode="DE" term="%22Object+recognition+%28Computer+vision%29%22">Object recognition (Computer vision)</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+vision%22">Computer vision</searchLink>
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  Data: While complex hands seem to offer generality, simple hands are often more practical. This raises the question: how do generality and simplicity trade off in the design of robot hands? This paper explores the tension between simplicity in hand design and generality in hand function. It raises arguments both for and against simple hands, it considers several familiar examples, and it proposes an approach for autonomous manipulation using a general-purpose but simple hand. We explore the approach in the context of a bin-picking task, focused on grasping, recognition, and localization. The central idea is to use learned knowledge of stable grasp poses as a cue for object recognition and localization. This leads to some novel design criteria, such as minimizing the number of stable grasp poses. Finally, we describe experiments with two prototype hands to perform bin-picking of highlighter markers. [ABSTRACT FROM PUBLISHER]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of International Journal of Robotics Research is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1177/0278364911429978
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        Text: English
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        Type: general
      – SubjectFull: Table manipulation (Computer science)
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      – SubjectFull: Machine theory
        Type: general
      – SubjectFull: Prototypes
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      – SubjectFull: Localization theory
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      – SubjectFull: Object recognition (Computer vision)
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            NameFull: Rodriguez, Alberto
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            NameFull: Srinivasa, Siddhartha S
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            NameFull: Vazquez, Andrés S
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              Text: May2012
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