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Grasping state estimation of printable soft gripper using electro-conductive yarn

Overview of attention for article published in Robotics and Biomimetics, November 2017
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Title
Grasping state estimation of printable soft gripper using electro-conductive yarn
Published in
Robotics and Biomimetics, November 2017
DOI 10.1186/s40638-017-0072-4
Pubmed ID
Authors

Takahiro Matsuno, Zhongkui Wang, Shinichi Hirai

Abstract

Automatic handling of many types of food materials are required to realize the automation of production of commercially prepared box lunches. A printable soft gripper was developed for food handling which is simple to produce with a 3D printer. However, the sensing ability of the printable soft gripper was not discussed in previous research. In this paper, a novel method for estimating the grasping state of a printable soft gripper using electro-conductive yarn is presented. Electro-conductive yarn is a conductive material, and the resistance of strings is changed by stretching. It is less expensive than other sensors that can be used for measurement of grasping state. Additionally, it is easy to assemble and disassemble by hand. Electro-conductive yarn is applied to a prototype printable soft gripper, and the proposed estimation method is verified experimentally. From the experimental results, the estimated grasping state from the resistance of the electro-conductive yarn coincides with the actual grasping state of the gripper. Our proposed method of using electro-conductive yarn was successful for estimating the grasping state of a printable soft gripper.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 4 25%
Student > Ph. D. Student 2 13%
Lecturer 1 6%
Student > Bachelor 1 6%
Researcher 1 6%
Other 0 0%
Unknown 7 44%
Readers by discipline Count As %
Engineering 9 56%
Medicine and Dentistry 1 6%
Unknown 6 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 10 November 2017.
All research outputs
#15,483,026
of 23,007,887 outputs
Outputs from Robotics and Biomimetics
#19
of 39 outputs
Outputs of similar age
#207,465
of 331,173 outputs
Outputs of similar age from Robotics and Biomimetics
#8
of 16 outputs
Altmetric has tracked 23,007,887 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 39 research outputs from this source. They receive a mean Attention Score of 1.8. This one scored the same or higher as 20 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 331,173 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.