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Satoko Nagakari

dblp:274/9754 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—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 · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › grasping › grasp control
grasp force control
0.412020
Theoretical Derivation and Realization of Adaptive Grasping Based on Rotational Incipient Slip Detection · ICRA 2020
Robotics › Robot manipulation
grasping
0.412020
Theoretical Derivation and Realization of Adaptive Grasping Based on Rotational Incipient Slip Detection · ICRA 2020
Robotics › Robot manipulation › tactile sensing › slip detection
incipient slip detection
0.412020
Theoretical Derivation and Realization of Adaptive Grasping Based on Rotational Incipient Slip Detection · ICRA 2020

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

theoretical slip model · 0.4sensor design · 0.4
YearPublicationVenuePosition
2020 Theoretical Derivation and Realization of Adaptive Grasping Based on Rotational Incipient Slip Detection
abstract
Manipulating objects whose physical properties are unknown remains one of the greatest challenges in robotics. Controlling grasp force is an essential aspect of handling unknown objects without slipping or crushing them. Although extensive research has been carried out on grasp force control, unknown object manipulation is still difficult because conventional approaches assume that object properties (mass, center of gravity, friction coefficient, etc.) are known for grasp force control. One of the approaches to address this issue is incipient slip detection. However, there has been few detailed investigations of robust detection and control of incipient slip on rotational case. This study makes contributions on deriving the theoretical model of incipient slip and proposes a new algorithm to detect incipient slip. Additionally, a novel sensor configuration and a grasp force control algorithm based on the derived theoretical model are proposed. Finally, the proposed algorithm is evaluated by grasping objects with different weights and moments including a fragile pastry (éclair).
Tetsuya Narita, Satoko Nagakari, William Conus, Toshimitsu Tsuboi, Ken'ichiro Nagasaka
ICRA2