Juntaro Tamura

dblp:234/8522 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › nonprehensile manipulation
dynamic manipulation
0.412019
Dynamic Manipulation of Flexible Objects with Torque Sequence Using a Deep Neural Network · ICRA 2019
Robotics › Robot manipulation › deformable object manipulation
flexible object manipulation
0.412019
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
0.112019
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
YearPublicationVenuePosition
2019 Dynamic Manipulation of Flexible Objects with Torque Sequence Using a Deep Neural Network
abstract
For 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
ICRA3