Demo Data from VLDB 2026 / reviewers in the wild / expert
Yuichi Lim
dblp:71/1608
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1
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 · 54% Motion planning and robot control · 46% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › locomotion control
CPG-based control |
0.0 | 1 | 2004 | CPG-based Manipulation: Generation of Rhythmic Finger Gaits from Human Observation · ICRA 2004 |
Robotics › Robot manipulation
dexterous manipulation |
0.0 | 1 | 2004 | CPG-based Manipulation: Generation of Rhythmic Finger Gaits from Human Observation · ICRA 2004 |
Robotics › Robot manipulation › dexterous manipulation
multi-fingered manipulation |
0.0 | 1 | 2004 | CPG-based Manipulation: Generation of Rhythmic Finger Gaits from Human Observation · ICRA 2004 |
Robotics › Motion planning and robot control
robot control |
0.0 | 1 | 2004 | CPG-based Manipulation: Generation of Rhythmic Finger Gaits from Human Observation · ICRA 2004 |
Methods — techniques the papers use, named apart from their topics
neural circuit model · 0.0central pattern generator · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2004 | CPG-based Manipulation: Generation of Rhythmic Finger Gaits from Human ObservationabstractA number of researches for the dexterous manipulation have been studied in robotics and physiologic fields independently. Multi-fingered manipulation for dexterous robot hands should be based on analysis of human skills. The purpose of this study is to apply CPG-based control to the dexterous manipulation. In this paper, CPG-based manipulation is proposed for the rotating manipulation of the dexterous hands. Finger manipulation patterns are investigated when a subject rotates a cylindrical object. Typical contact patterns during rotating manipulation are measured by FSRs. Based on the observation, the neural circuit model which generates a similar contact pattern is constructed. The experimental results by the computer simulation suggest that rotating manipulation can be performed using the constructed CPG model. Yuichi Kurita, Yuichi Lim, Jun Ueda, Yoshio Matsumoto, Tsukasa Ogasawara |
ICRA | 2 |