EDBT 2026 Demo / reviewers in the wild / expert
Juntaro Tamura
dblp:234/8522
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—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 · 87% Motion planning and robot control · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation › nonprehensile manipulation
dynamic manipulation |
0.4 | 1 | 2019 | Dynamic Manipulation of Flexible Objects with Torque Sequence Using a Deep Neural Network · ICRA 2019 |
Robotics › Robot manipulation › deformable object manipulation
flexible object manipulation |
0.4 | 1 | 2019 | Dynamic Manipulation of Flexible Objects with Torque Sequence Using a Deep Neural Network · ICRA 2019 |
Robotics › Motion planning and robot control › robot control
torque control |
0.1 | 1 | 2019 | Dynamic Manipulation of Flexible Objects with Torque Sequence Using a Deep Neural Network · ICRA 2019 |
Methods — techniques the papers use, named apart from their topics
time-series joint torque optimization · 0.4deep neural network · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Dynamic Manipulation of Flexible Objects with Torque Sequence Using a Deep Neural NetworkabstractFor dynamic manipulation of flexible objects, we propose an acquisition method of a flexible object motion equation model using a deep neural network and a control method to realize a target state by calculating an optimized time-series joint torque command. By using the proposed method, any physics model of a target object is not needed, and the object can be controlled as intended. We applied this method to manipulations of a rigid object, a flexible object with and without environmental contact, and a cloth, and verified its effectiveness. Kento Kawaharazuka, Toru Ogawa, Juntaro Tamura, Cota Nabeshima |
ICRA | 3 |