Cuo Yan

dblp:324/6235 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

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
Motion planning and robot control · 56% Robot manipulation · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › dexterous manipulation
in-hand manipulation
0.612022
Negative Stiffness Analysis and Regulation of In-Hand Manipulation with Underactuated Compliant Hands · ICRA 2022
Robotics › Motion planning and robot control › robot control › impedance control
stiffness control
0.612022
Negative Stiffness Analysis and Regulation of In-Hand Manipulation with Underactuated Compliant Hands · ICRA 2022
Robotics › Motion planning and robot control › robot control › underactuated systems
underactuated object manipulation
0.212022
Negative Stiffness Analysis and Regulation of In-Hand Manipulation with Underactuated Compliant Hands · ICRA 2022

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

stiffness regulation · 0.6quasi-static underactuated operation model · 0.6
YearPublicationVenuePosition
2022 Negative Stiffness Analysis and Regulation of In-Hand Manipulation with Underactuated Compliant Hands
abstract
This paper addresses the generation mechanism and avoidance method of negative stiffness during in-Hand manipulation with underactuated compliant hands. Firstly, a planar hand with two three-jointed fingers manipulating a rectangular is set, and a quasi-static underactuated operation model is established. Secondly, based on this simulation model, we investigated the stiffness evolution during in-hand manipulation, and analyze the influence factors of system stiffness. Finally, a stiffness regulation method is developed to avoid negative stiffness during in-hand manipulation. The method is validated by simulation. The research results are beneficial to improve the performance of underactuated in-hand manipulation.
Wenrui Chen, Qiang Diao, Yaonan Wang 0001, Cuo Yan, Zhiyong Li 0001
ICRA6