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KLT Bin Detection and Pose Estimation in an Industrial Environment. / Beloshapko, Aleksei; Knoll, Christian; Boughattas, Bilel; Korkhov, Vladimir.
Computational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings. ред. / Osvaldo Gervasi; Beniamino Murgante; Sanjay Misra; Chiara Garau; Ivan Blecic; David Taniar; Bernady O. Apduhan; Ana Maria A.C. Rocha; Eufemia Tarantino; Carmelo Maria Torre; Yeliz Karaca. Springer Nature, 2020. стр. 105-118 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 12254 LNCS).
Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Harvard
Beloshapko, A, Knoll, C, Boughattas, B
& Korkhov, V 2020,
KLT Bin Detection and Pose Estimation in an Industrial Environment. в O Gervasi, B Murgante, S Misra, C Garau, I Blecic, D Taniar, BO Apduhan, AMAC Rocha, E Tarantino, CM Torre & Y Karaca (ред.),
Computational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том. 12254 LNCS, Springer Nature, стр. 105-118, 20th International Conference on Computational Science and Its Applications, ICCSA 2020, Cagliari, Италия,
1/07/20.
https://doi.org/10.1007/978-3-030-58817-5_9
APA
Beloshapko, A., Knoll, C., Boughattas, B.
, & Korkhov, V. (2020).
KLT Bin Detection and Pose Estimation in an Industrial Environment. в O. Gervasi, B. Murgante, S. Misra, C. Garau, I. Blecic, D. Taniar, B. O. Apduhan, A. M. A. C. Rocha, E. Tarantino, C. M. Torre, & Y. Karaca (Ред.),
Computational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings (стр. 105-118). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 12254 LNCS). Springer Nature.
https://doi.org/10.1007/978-3-030-58817-5_9
Vancouver
Beloshapko A, Knoll C, Boughattas B
, Korkhov V.
KLT Bin Detection and Pose Estimation in an Industrial Environment. в Gervasi O, Murgante B, Misra S, Garau C, Blecic I, Taniar D, Apduhan BO, Rocha AMAC, Tarantino E, Torre CM, Karaca Y, Редакторы, Computational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings. Springer Nature. 2020. стр. 105-118. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
https://doi.org/10.1007/978-3-030-58817-5_9
Author
Beloshapko, Aleksei ; Knoll, Christian ; Boughattas, Bilel
; Korkhov, Vladimir. /
KLT Bin Detection and Pose Estimation in an Industrial Environment. Computational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings. Редактор / Osvaldo Gervasi ; Beniamino Murgante ; Sanjay Misra ; Chiara Garau ; Ivan Blecic ; David Taniar ; Bernady O. Apduhan ; Ana Maria A.C. Rocha ; Eufemia Tarantino ; Carmelo Maria Torre ; Yeliz Karaca. Springer Nature, 2020. стр. 105-118 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
BibTeX
@inproceedings{24b9f149fe1044e0aee9b421bc10b245,
title = "KLT Bin Detection and Pose Estimation in an Industrial Environment",
abstract = "In order for Automated Guided Vehicles (AGV{\textquoteright}s) to handle KLT bins (Kleinladungstr{\"a}ger, Small Load Carrier) in a flexible way, a robust bin detection algorithm has to be developed. This paper presents a solution to the KLT bin detection and pose estimation task. The Mask R-CNN network is used to detect a KLT bin on color images, while a simple plane fitting approach is used to estimate its 5DoF position. This combination gives promising results in a typical use case scenario when the KLT bin is aligned with the camera view.",
keywords = "Industry 4.0, Instance segmentation, KLT bin picking, Object detection, Plane fitting, Pose estimation",
author = "Aleksei Beloshapko and Christian Knoll and Bilel Boughattas and Vladimir Korkhov",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 20th International Conference on Computational Science and Its Applications, ICCSA 2020 ; Conference date: 01-07-2020 Through 04-07-2020",
year = "2020",
doi = "10.1007/978-3-030-58817-5_9",
language = "English",
isbn = "9783030588168",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "105--118",
editor = "Osvaldo Gervasi and Beniamino Murgante and Sanjay Misra and Chiara Garau and Ivan Blecic and David Taniar and Apduhan, {Bernady O.} and Rocha, {Ana Maria A.C.} and Eufemia Tarantino and Torre, {Carmelo Maria} and Yeliz Karaca",
booktitle = "Computational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings",
address = "Germany",
url = "http://iccsa.org/",
}
RIS
TY - GEN
T1 - KLT Bin Detection and Pose Estimation in an Industrial Environment
AU - Beloshapko, Aleksei
AU - Knoll, Christian
AU - Boughattas, Bilel
AU - Korkhov, Vladimir
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - In order for Automated Guided Vehicles (AGV’s) to handle KLT bins (Kleinladungsträger, Small Load Carrier) in a flexible way, a robust bin detection algorithm has to be developed. This paper presents a solution to the KLT bin detection and pose estimation task. The Mask R-CNN network is used to detect a KLT bin on color images, while a simple plane fitting approach is used to estimate its 5DoF position. This combination gives promising results in a typical use case scenario when the KLT bin is aligned with the camera view.
AB - In order for Automated Guided Vehicles (AGV’s) to handle KLT bins (Kleinladungsträger, Small Load Carrier) in a flexible way, a robust bin detection algorithm has to be developed. This paper presents a solution to the KLT bin detection and pose estimation task. The Mask R-CNN network is used to detect a KLT bin on color images, while a simple plane fitting approach is used to estimate its 5DoF position. This combination gives promising results in a typical use case scenario when the KLT bin is aligned with the camera view.
KW - Industry 4.0
KW - Instance segmentation
KW - KLT bin picking
KW - Object detection
KW - Plane fitting
KW - Pose estimation
UR - http://www.scopus.com/inward/record.url?scp=85092609797&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/339668e0-c75d-359a-948f-3c924ef2e424/
U2 - 10.1007/978-3-030-58817-5_9
DO - 10.1007/978-3-030-58817-5_9
M3 - Conference contribution
AN - SCOPUS:85092609797
SN - 9783030588168
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 105
EP - 118
BT - Computational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings
A2 - Gervasi, Osvaldo
A2 - Murgante, Beniamino
A2 - Misra, Sanjay
A2 - Garau, Chiara
A2 - Blecic, Ivan
A2 - Taniar, David
A2 - Apduhan, Bernady O.
A2 - Rocha, Ana Maria A.C.
A2 - Tarantino, Eufemia
A2 - Torre, Carmelo Maria
A2 - Karaca, Yeliz
PB - Springer Nature
T2 - 20th International Conference on Computational Science and Its Applications, ICCSA 2020
Y2 - 1 July 2020 through 4 July 2020
ER -
