Reasoning about grasping from task descriptions

Huan Liu; Thea Iberall; George A. Bekey

doi:10.1117/12.960326

Reasoning about grasping from task descriptions

Huan Liu, Thea Iberall, George A. Bekey

Research output: Contribution to journal › Conference article › peer-review

Abstract

The advent of multiple degree of freedom, dextrous robot hands has made robot hand control more complicated. Besides the existing problem of finding a suitable grasping position and approach orientation, it is now necessary to decide the appropriate hand shape to use for a given task. In order to deal with this additional complexity, we focus on how to represent prehensile tasks for mapping task descriptions into suitable hand shapes, positions and orientations. A generic robot hand control system GeSAM is being implemented to refine task descriptions into suitable dextrous robot hand shapes using Knowledge Craft on a TI lisp machine.

Original language	English (US)
Pages (from-to)	642-651
Number of pages	10
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	1002
DOIs	https://doi.org/10.1117/12.960326
State	Published - Mar 27 1989
Externally published	Yes
Event	Intelligent Robots and Computer Vision VII 1988 - Boston, United States Duration: Nov 7 1988 → Nov 11 1988

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

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10.1117/12.960326

Cite this

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title = "Reasoning about grasping from task descriptions",

abstract = "The advent of multiple degree of freedom, dextrous robot hands has made robot hand control more complicated. Besides the existing problem of finding a suitable grasping position and approach orientation, it is now necessary to decide the appropriate hand shape to use for a given task. In order to deal with this additional complexity, we focus on how to represent prehensile tasks for mapping task descriptions into suitable hand shapes, positions and orientations. A generic robot hand control system GeSAM is being implemented to refine task descriptions into suitable dextrous robot hand shapes using Knowledge Craft on a TI lisp machine.",

author = "Huan Liu and Thea Iberall and Bekey, {George A.}",

note = "Funding Information: This research was funded in part by grants from the Institute for Manufacturing and Automation Research, NSF-IMAR #CDR-871-7322, and the Division of Research Resources of the NIH #5-P41-RR01861-03. We would like to thank Iljia Zeljkovic for his help in integrating this system with the Belgrade/USC hand. Publisher Copyright: {\textcopyright} 1989 SPIE. All rights reserved.; Intelligent Robots and Computer Vision VII 1988 ; Conference date: 07-11-1988 Through 11-11-1988",

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day = "27",

doi = "10.1117/12.960326",

language = "English (US)",

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journal = "Proceedings of SPIE - The International Society for Optical Engineering",

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T1 - Reasoning about grasping from task descriptions

AU - Liu, Huan

AU - Iberall, Thea

AU - Bekey, George A.

N1 - Funding Information: This research was funded in part by grants from the Institute for Manufacturing and Automation Research, NSF-IMAR #CDR-871-7322, and the Division of Research Resources of the NIH #5-P41-RR01861-03. We would like to thank Iljia Zeljkovic for his help in integrating this system with the Belgrade/USC hand. Publisher Copyright: © 1989 SPIE. All rights reserved.

PY - 1989/3/27

Y1 - 1989/3/27

N2 - The advent of multiple degree of freedom, dextrous robot hands has made robot hand control more complicated. Besides the existing problem of finding a suitable grasping position and approach orientation, it is now necessary to decide the appropriate hand shape to use for a given task. In order to deal with this additional complexity, we focus on how to represent prehensile tasks for mapping task descriptions into suitable hand shapes, positions and orientations. A generic robot hand control system GeSAM is being implemented to refine task descriptions into suitable dextrous robot hand shapes using Knowledge Craft on a TI lisp machine.

AB - The advent of multiple degree of freedom, dextrous robot hands has made robot hand control more complicated. Besides the existing problem of finding a suitable grasping position and approach orientation, it is now necessary to decide the appropriate hand shape to use for a given task. In order to deal with this additional complexity, we focus on how to represent prehensile tasks for mapping task descriptions into suitable hand shapes, positions and orientations. A generic robot hand control system GeSAM is being implemented to refine task descriptions into suitable dextrous robot hand shapes using Knowledge Craft on a TI lisp machine.

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M3 - Conference article

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JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Intelligent Robots and Computer Vision VII 1988

Y2 - 7 November 1988 through 11 November 1988

ER -

Reasoning about grasping from task descriptions

Abstract

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