Demo Data from EDBT 2026 / reviewers in the wild / expert
Takahashi Maeno
dblp:94/3600
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation › contact modeling
friction coefficient estimation |
0.0 | 1 | 2003 | 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 |
0.0 | 1 | 2003 | 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 |
0.0 | 1 | 2003 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | Geometry design of an elastic finger-shaped sensor for estimating friction coefficient by pressing any objectabstractThe 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 |
ICRA | 1 |