| Title |
Grasp quality measures: review and performance
|
|---|---|
| Published in |
Autonomous Robots, July 2014
|
| DOI | 10.1007/s10514-014-9402-3 |
| Pubmed ID | |
| Authors |
Máximo A. Roa, Raúl Suárez |
| Abstract |
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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 360 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 2% |
| United Kingdom | 1 | <1% |
| Canada | 1 | <1% |
| Spain | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| Greece | 1 | <1% |
| Japan | 1 | <1% |
| Unknown | 348 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 106 | 29% |
| Student > Master | 57 | 16% |
| Researcher | 46 | 13% |
| Student > Doctoral Student | 22 | 6% |
| Student > Bachelor | 22 | 6% |
| Other | 39 | 11% |
| Unknown | 68 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 184 | 51% |
| Computer Science | 77 | 21% |
| Unspecified | 7 | 2% |
| Business, Management and Accounting | 1 | <1% |
| Agricultural and Biological Sciences | 1 | <1% |
| Other | 8 | 2% |
| Unknown | 82 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 November 2021.
All research outputs
#6,941,088
of 22,759,618 outputs
Outputs from Autonomous Robots
#117
of 518 outputs
Outputs of similar age
#66,021
of 228,346 outputs
Outputs of similar age from Autonomous Robots
#3
of 23 outputs
Altmetric has tracked 22,759,618 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 518 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 77% of its peers.
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We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.