Data-Driven Object Pose Estimation in a Practical Bin-Picking Application
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00352836" target="_blank" >RIV/68407700:21230/21:00352836 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/21:00352836
Result on the web
<a href="https://doi.org/10.3390/s21186093" target="_blank" >https://doi.org/10.3390/s21186093</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/s21186093" target="_blank" >10.3390/s21186093</a>
Alternative languages
Result language
angličtina
Original language name
Data-Driven Object Pose Estimation in a Practical Bin-Picking Application
Original language description
This paper addresses the problem of pose estimation from 2D images for textureless industrial metallic parts for a semistructured bin-picking task. The appearance of metallic reflective parts is highly dependent on the camera viewing direction, as well as the distribution of light on the object, making conventional vision-based methods unsuitable for the task. We propose a solution using direct light at a fixed position to the camera, mounted directly on the robot's gripper, that allows us to take advantage of the reflective properties of the manipulated object. We propose a data-driven approach based on convolutional neural networks (CNN), without the need for a hard-coded geometry of the manipulated object. The solution was modified for an industrial application and extensively tested in a real factory. Our solution uses a cheap 2D camera and allows for a semi-automatic data-gathering process on-site.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF15_003%2F0000470" target="_blank" >EF15_003/0000470: Robotics 4 Industry 4.0</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Sensors
ISSN
1424-8220
e-ISSN
1424-8220
Volume of the periodical
21
Issue of the periodical within the volume
18
Country of publishing house
CH - SWITZERLAND
Number of pages
23
Pages from-to
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UT code for WoS article
000701557400001
EID of the result in the Scopus database
2-s2.0-85114601266