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Yuichi Lim

dblp:71/1608 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › locomotion control
CPG-based control
0.012004
CPG-based Manipulation: Generation of Rhythmic Finger Gaits from Human Observation · ICRA 2004
Robotics › Robot manipulation
dexterous manipulation
0.012004
CPG-based Manipulation: Generation of Rhythmic Finger Gaits from Human Observation · ICRA 2004
Robotics › Robot manipulation › dexterous manipulation
multi-fingered manipulation
0.012004
CPG-based Manipulation: Generation of Rhythmic Finger Gaits from Human Observation · ICRA 2004
Robotics › Motion planning and robot control
robot control
0.012004
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
YearPublicationVenuePosition
2004 CPG-based Manipulation: Generation of Rhythmic Finger Gaits from Human Observation
abstract
A 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
ICRA2