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Takahashi Maeno

dblp:94/3600 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2003
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › contact modeling
friction coefficient estimation
0.012003
Geometry design of an elastic finger-shaped sensor for estimating friction coefficient by pressing any object · ICRA 2003
Robotics › Robot manipulation › tactile sensing
tactile sensing for manipulation
0.012003
Geometry design of an elastic finger-shaped sensor for estimating friction coefficient by pressing any object · ICRA 2003
Robotics › Robot manipulation › tactile sensing
tactile sensor design
0.012003
Geometry design of an elastic finger-shaped sensor for estimating friction coefficient by pressing any object · ICRA 2003

Methods — techniques the papers use, named apart from their topics

strain gage sensing · 0.0finite element analysis · 0.0
YearPublicationVenuePosition
2003 Geometry design of an elastic finger-shaped sensor for estimating friction coefficient by pressing any object
abstract
The authors have proposed a method for detecting a friction coefficient between a planar object and an elastic finger-shaped sensor by only pressing the sensor against the object in our previous study. In the present study, an elastic finger-shaped sensor made of silicone rubber is designed and produced. First, geometry of the finger-shaped sensor is designed using finite element analysis (FEA). Results of FEA revealed that strain detected using strain gage incorporated near the edge of the contact surface varies when the friction coefficient between the finger-based sensor and a planar object varies. Then, in a experiment using the newly designed sensor, it is confirmed that the friction coefficient between the finger and the object is detected using the strain inside the finger when the sensor is pressed against the object.
Takahashi Maeno, Tomoyuki Kawamura
ICRA1