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Trinh Van Vinh

dblp:117/2318 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

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 · 61% Motion planning and robot control · 39%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
deformable object manipulation
0.112012
A new strategy for making a knot with a general-purpose arm · ICRA 2012
Robotics › Robot manipulation › deformable object manipulation
knot tying
0.112012
A new strategy for making a knot with a general-purpose arm · ICRA 2012
Robotics › Motion planning and robot control › robot learning
manipulation skill learning
0.112012
A new strategy for making a knot with a general-purpose arm · ICRA 2012
Robotics › Motion planning and robot control
trajectory planning
0.012012
A new strategy for making a knot with a general-purpose arm · ICRA 2012

Methods — techniques the papers use, named apart from their topics

skill synthesis · 0.1motion primitive extraction · 0.1
YearPublicationVenuePosition
2012 A new strategy for making a knot with a general-purpose arm
abstract
This paper proposes a new strategy for making a knot with a general-purpose arm. The strategy is divided into four stages: First, a human-performed knotting action is analyzed to acquire some motion primitives. Second, based on these databases, the robot is taught to tie a knot. Third, key points on the stored trajectories are extracted. These key points are considered in a general case, and then used to implement the manipulation skills. Finally, knotting task is generated by synthesis of the manipulation skills. An overhand knot was made by the actual robot for the validity of the proposed method. This paper also describes a system for manipulating deformable objects (e.g. knotting a rope).
Trinh Van Vinh, Tetsuo Tomizawa, Shunsuke Kudoh, Takashi Suehiro
ICRA1