Demo Data from SIGIR 2026 / reviewers in the wild / expert
Moriyuki Sakamoto
dblp:36/2272
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1999
—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 · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation
dexterous manipulation |
0.0 | 1 | 1999 | Vision-Aided Object Manipulation by a Multifingered Hand with Soft Fingertips · ICRA 1999 |
Robotics › Robot manipulation › dexterous manipulation
multi-fingered manipulation |
0.0 | 1 | 1999 | Vision-Aided Object Manipulation by a Multifingered Hand with Soft Fingertips · ICRA 1999 |
Robotics › Robot manipulation
grasping |
0.0 | 1 | 1999 | Vision-Aided Object Manipulation by a Multifingered Hand with Soft Fingertips · ICRA 1999 |
Robotics › Robot manipulation › contact modeling
soft tip contact |
0.0 | 1 | 1999 | Vision-Aided Object Manipulation by a Multifingered Hand with Soft Fingertips · ICRA 1999 |
Methods — techniques the papers use, named apart from their topics
pose estimation · 0.0finger joint information · 0.0camera images · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1999 | Vision-Aided Object Manipulation by a Multifingered Hand with Soft FingertipsabstractSoft fingertips can easily achieve high friction contacts but their frictional moment around the contact normals makes manipulation control difficult. We propose a control scheme to manipulate an object by a multifingered hand with soft fingertips. The proposed scheme cancels the frictional moment according to the direction of the relative rotation between the fingertip and the object. Whatever the fingertip contact type is, accurate pose measurement is very important for the object manipulation. We also propose a systematic method to estimate the object pose with a complementary use of camera images and finger joint information. The proposed control scheme and the pose estimation method were combined and implemented in an experimental system. Results of the experiment show the effectiveness of the proposed pose estimation method and the overall control system for manipulating an object by a soft-fingered hand. Yasuyoshi Yokokohji, Moriyuki Sakamoto, Tsuneo Yoshikawa |
ICRA | 2 |