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Real-Time Implementation of Image Based PLC Control for a Robotic Platform

Year 2019, Volume: 7 Issue: 1, 64 - 71, 31.01.2019
https://doi.org/10.17694/bajece.487212

Abstract

In this study, image
based real-time control of a linear robotic platform was performed. This
robotic platform is used to determine the location of the mushroom and to
direct the linear platform to the detected position in real time with PLC
control. Haar-Cascade classifier was used to detect mushroom position and
Visual Studio C # .NET platform was used to test the Cascade classifier and
write other evaluation codes. One of the most important outputs of this work is
to determine the actual position in the global coordinate from the pixel-based
location of the object in the image using an ordinary USB camera or built-in
camera. Calibration technique was used for this determination
.

References

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  • [16] Y. M. Wang, Y. Li, ve J. B. Zheng, “A camera calibration technique based on OpenCV”, 3rd International Conference on Information Sciences and Interaction Sciences (ICIS 2010), Chengdu, China, ss. 403–406, 2010.
  • [17] E. Wood ve A. Bulling, “Eyetab: Model-based gaze estimation on unmodified tablet computers”, Proceedings of the Symposium on Eye Tracking …, ss. 3–6, 2014.
  • [18] Anonymous, “S7-1200 DataSheet”, 2012. [Online]. Available at: https://cache.industry.siemens.com/dl/files/465/36932465/att_106119/v1/s71200_system_manual_en-US_en-US.pdf. [Access: 20-Nov-2018].
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Year 2019, Volume: 7 Issue: 1, 64 - 71, 31.01.2019
https://doi.org/10.17694/bajece.487212

Abstract

References

  • [1] Anonymous, “Mantar yeti̇şti̇ri̇ci̇li̇ği̇”, ss. 2–5, 2017. [Online]. Available at: https://istanbul.tarim.gov.tr/Belgeler/KutuMenu/Brosurler/Sebzecilik/mantar.pdf. [Access: 27-Oct-2018].
  • [2] Y. A. Sari ve S. Adinugroho, “Tomato ripeness clustering using 6-means algorithm based on v-channel otsu segmentation”, 5th International Symposium on Computational and Business Intelligence, ISCBI 2017, ss. 32–36, 2017.
  • [3] S. SOLAK ve U. ALTINIŞIK, “Görüntü İşleme Teknikleri ve Kümeleme Yöntemleri Kullanılarak Fındık Meyvesinin Tespit ve Sınıflandırılması”, SAÜ Fen Bilimleri Enstitüsü Dergisi, c. 22, num. 1, ss. 1–1, 2018.
  • [4] M. S. A. Mahmud, M. S. Z. Abidin, ve Z. Mohamed, “Development of an autonomous crop inspection mobile robot system”, 2015 IEEE Student Conference on Research and Development, SCOReD 2015, ss. 105–110, 2015.
  • [5] S. S. Mehta ve T. F. Burks, “Adaptive Visual Servo Control of Robotic Harvesting Systems”, IFAC-PapersOnLine, c. 49, num. 16, ss. 287–292, 2016.
  • [6] Y. Zhao, L. Gong, Y. Huang, ve C. Liu, “A review of key techniques of vision-based control for harvesting robot”, Computers and Electronics in Agriculture, c. 127, ss. 311–323, 2016.
  • [7] W. Jun, Z. Zhou, ve D. U. Xiaodong, “Design and Co-simulation for Tomato Harvesting Robots”, Proceedings of the 31st Chinese Control Conference, ss. 5105–5108, 2012.
  • [8] B. Li, M. Wang, ve L. Li, “A real-time pineapple matching system based on speeded-up robust features”, Proceedings - 2010 International Conference on Computational Intelligence and Security, CIS 2010, ss. 243–247, 2010.
  • [9] Q. Feng, X. Wang, G. Wang, ve Z. Li, “Design and test of tomatoes harvesting robot”, 2015 IEEE International Conference on Information and Automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on Automation and Logistics, num. August, ss. 949–952, 2015.
  • [10] A. Masoudian, “COMPUTER VISION ALGORITHMS FOR AN AUTOMATED HARVESTER (Thesis format: Monograph)”, num. December, 2013.
  • [11] A. Shaikh, G. Khaladkar, R. Jage, ve T. P. J. Taili, “Robotic Arm Movements Wirelessly Synchronized with Human Arm Movements Using Real Time Image Processing”, 2013 Texas Instruments India Educators’ Conference, ss. 277–284, 2013.
  • [12] M. Enzweiler ve D. M. Gavrila, “Monocular pedestrian detection: Survey and experiments”, IEEE Transactions on Pattern Analysis and Machine Intelligence, c. 31, num. 12, ss. 2179–2195, 2009.
  • [13] C. R. Wren, A. Azarbayejani, T. Darrell, ve A. P. Pentland, “Pfinder: real-time tracking of the human body”, IEEE Transactions on Pattern Analysis and Machine Intelligence, c. 19, num. 7, ss. 780–785, 1997.
  • [14] P. Viola ve M. Jones, “Rapid object detection using a boosted cascade of simple features”, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, c. 1, s. I-511-I-518, 2001.
  • [15] C. Olsson, “Lecture 1 : The Pinhole Camera Model”, c. 3, num. 2, ss. 2–5, 2013.
  • [16] Y. M. Wang, Y. Li, ve J. B. Zheng, “A camera calibration technique based on OpenCV”, 3rd International Conference on Information Sciences and Interaction Sciences (ICIS 2010), Chengdu, China, ss. 403–406, 2010.
  • [17] E. Wood ve A. Bulling, “Eyetab: Model-based gaze estimation on unmodified tablet computers”, Proceedings of the Symposium on Eye Tracking …, ss. 3–6, 2014.
  • [18] Anonymous, “S7-1200 DataSheet”, 2012. [Online]. Available at: https://cache.industry.siemens.com/dl/files/465/36932465/att_106119/v1/s71200_system_manual_en-US_en-US.pdf. [Access: 20-Nov-2018].
  • [19] Anonymous, “S7.Net documentation Create a PLC instance , connect and disconnect”, 2016. [Online]. Available at: https://github.com/S7NetPlus/s7netplus/blob/master/Documentation/Documentation.pdf. [Access: 23-Sep-2018].
There are 19 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Araştırma Articlessi
Authors

Kağan Koray Ayten 0000-0002-8933-612X

Publication Date January 31, 2019
Published in Issue Year 2019 Volume: 7 Issue: 1

Cite

APA Ayten, K. K. (2019). Real-Time Implementation of Image Based PLC Control for a Robotic Platform. Balkan Journal of Electrical and Computer Engineering, 7(1), 64-71. https://doi.org/10.17694/bajece.487212

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