Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
The GRASP Taxonomy of Human Grasp Types
Show others and affiliations
2016 (English)In: IEEE Transactions on Human-Machine Systems, ISSN 2168-2291, E-ISSN 2168-2305, Vol. 46, no 1, p. 66-77Article in journal (Refereed) Published
Resource type
Text
Abstract [en]

In this paper, we analyze and compare existing human grasp taxonomies and synthesize them into a single new taxonomy (dubbed "The GRASP Taxonomy" after the GRASP project funded by the European Commission). We consider only static and stable grasps performed by one hand. The goal is to extract the largest set of different grasps that were referenced in the literature and arrange them in a systematic way. The taxonomy provides a common terminology to define human hand configurations and is important in many domains such as human-computer interaction and tangible user interfaces where an understanding of the human is basis for a proper interface. Overall, 33 different grasp types are found and arranged into the GRASP taxonomy. Within the taxonomy, grasps are arranged according to 1) opposition type, 2) the virtual finger assignments, 3) type in terms of power, precision, or intermediate grasp, and 4) the position of the thumb. The resulting taxonomy incorporates all grasps found in the reviewed taxonomies that complied with the grasp definition. We also show that due to the nature of the classification, the 33 grasp types might be reduced to a set of 17 more general grasps if only the hand configuration is considered without the object shape/size.

Place, publisher, year, edition, pages
IEEE , 2016. Vol. 46, no 1, p. 66-77
Keywords [en]
Hand/wrist posture, human-robot interaction, taxonomies, robotics, human factors
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-182772DOI: 10.1109/THMS.2015.2470657ISI: 000368829400006OAI: oai:DiVA.org:kth-182772DiVA, id: diva2:906085
Note

QC 20160223

Available from: 2016-02-23 Created: 2016-02-23 Last updated: 2018-01-10Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Kragic, Danica

Search in DiVA

By author/editor
Kragic, Danica
By organisation
Centre for Autonomous Systems, CASComputer Vision and Active Perception, CVAP
In the same journal
IEEE Transactions on Human-Machine Systems
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 227 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf