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Jakub Cmiral

dblp:226/6452 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—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
3D vision · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › inverse rendering
material property estimation
0.312018
Automatic Material Properties Estimation for the Physics-Based Robotic Garment Folding · ICRA 2018
Computer vision › 3D vision
physical simulation
0.312018
Automatic Material Properties Estimation for the Physics-Based Robotic Garment Folding · ICRA 2018

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

laser range finder · 0.3iterative optimization · 0.3
YearPublicationVenuePosition
2018 Automatic Material Properties Estimation for the Physics-Based Robotic Garment Folding
abstract
The estimation of the fabric material property during the folding is presented. The available techniques for the accurate garment folding rely on known material properties. Currently, the properties are estimated by an operator in advance of folding. We propose an iterative strategy, which updates the property while the garment is folded. The estimation is formulated as an optimisation task. It is based on measurements from a laser range finder. The proposed algorithm improves the estimation iteratively and prevents the garment from slipping at the same time. We demonstrate the estimation procedure for 10 fabric strips of different materials.
Vladimír Petrík, Jakub Cmiral, Vladimír Smutný, Pavel Krsek, Václav Hlavác
ICRA2