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Grasp quality measures: review and performance
by
Roa, Máximo A.
, Suárez, Raúl
in
Algorithms
/ Artificial Intelligence
/ Autonomous
/ Computer Imaging
/ Contact
/ Control
/ Engineering
/ Human
/ Mechatronics
/ Pattern Recognition and Graphics
/ Robotics
/ Robotics and Automation
/ Robots
/ Tasks
/ Vision
2015
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Grasp quality measures: review and performance
by
Roa, Máximo A.
, Suárez, Raúl
in
Algorithms
/ Artificial Intelligence
/ Autonomous
/ Computer Imaging
/ Contact
/ Control
/ Engineering
/ Human
/ Mechatronics
/ Pattern Recognition and Graphics
/ Robotics
/ Robotics and Automation
/ Robots
/ Tasks
/ Vision
2015
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Do you wish to request the book?
Grasp quality measures: review and performance
by
Roa, Máximo A.
, Suárez, Raúl
in
Algorithms
/ Artificial Intelligence
/ Autonomous
/ Computer Imaging
/ Contact
/ Control
/ Engineering
/ Human
/ Mechatronics
/ Pattern Recognition and Graphics
/ Robotics
/ Robotics and Automation
/ Robots
/ Tasks
/ Vision
2015
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Journal Article
Grasp quality measures: review and performance
2015
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Overview
The correct grasp of objects is a key aspect for the right fulfillment of a given task. Obtaining a good grasp requires algorithms to automatically determine proper contact points on the object as well as proper hand configurations, especially when dexterous manipulation is desired, and the quantification of a good grasp requires the definition of suitable grasp quality measures. This article reviews the quality measures proposed in the literature to evaluate grasp quality. The quality measures are classified into two groups according to the main aspect they evaluate: location of contact points on the object and hand configuration. The approaches that combine different measures from the two previous groups to obtain a global quality measure are also reviewed, as well as some measures related to human hand studies and grasp performance. Several examples are presented to illustrate and compare the performance of the reviewed measures.
Publisher
Springer US,Springer Nature B.V
Subject
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