Demo Data from EDBT 2026 / reviewers in the wild / expert
Masaki Fujiwara
dblp:61/5202
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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 · 50% Motion planning and robot control · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot dynamics › dynamic performance analysis
dynamic manipulability |
0.1 | 1 | 2009 | Dynamic Manipulability of Multifingered Grasping · IEEE Trans. Robotics 2009 |
Robotics › Robot manipulation
grasping |
0.1 | 1 | 2009 | Dynamic Manipulability of Multifingered Grasping · IEEE Trans. Robotics 2009 |
Robotics › Robot manipulation › grasping
multifingered grasping |
0.1 | 1 | 2009 | Dynamic Manipulability of Multifingered Grasping · IEEE Trans. Robotics 2009 |
Robotics › Motion planning and robot control
robot control |
0.1 | 1 | 2009 | Dynamic Manipulability of Multifingered Grasping · IEEE Trans. Robotics 2009 |
Methods — techniques the papers use, named apart from their topics
ellipsoid-based manipulability analysis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | Dynamic Manipulability of Multifingered GraspingabstractIn this paper, we extend the concept of dynamic manipulability to evaluate the dynamic property of multifingered grasping systems consisting of a multifingered hand and a grasped object, and propose a measure of dynamic manipulability of multifingered grasping. Similar to the original dynamic manipulability, the proposed measure evaluates the mapping from a set of realizable joint torques to a set of resultant accelerations of the grasped object, which forms an ellipsoid under a constant internal force constraint. It is clearly shown that the internal forces not only affect the volume of the ellipsoid, but also the amount of offset of the ellipsoid, while the gravity forces simply induce an offset. A new measure, i.e., omnidirectionality, is introduced to add a penalty to the original manipulability measure, which simply evaluates the volume of the ellipsoid, depending on how much the ellipsoid is offset. Numerical examples by using a simple two-fingered robot hand are shown to demonstrate the effectiveness of the proposed measure. Yasuyoshi Yokokohji, Jose San Martin, Masaki Fujiwara |
IEEE Trans. Robotics | 3 |