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Automatic Object Painting with SCARA Robot Using Computer Vision

Year 2018, Volume: 14 Issue: 1, 17 - 22, 30.03.2018
https://doi.org/10.18466/cbayarfbe.306950

Abstract

Recognizing and accurately classifying colors in industrial applications is a critical challenge in developing robotics painting applications. To achieve this, many painting robots are attached with expensive color sensors. However, these sensors are coming with many drawbacks such as color ranges limitation and sensitivity to illumination in addition to their high costs. In the last decades, camera systems gained importance in robotics applications with the power presented by the computer vision techniques. The main objective of this paper is to design an automation line that includes a robot and camera system to perform painting in different colors, with various illumination conditions at cheaper costs. The proposed system can be used to paint multiple colors effectively and accurately. The power of the system comes from the color detection and classification algorithm that is designed using computer vision techniques. The algorithm is designed under C++ environment using OpenCV library. The system will able to detect all colors that are adjusted/predefined offline by the user and to work in different illumination conditions. The end-effector of the robot consists of two main parts, a camera to detect the desired color and an automatic spray gun to perform the painting operation. The proposed system detects will do so based on a small sticker pasted on the object that will be painted. When the desired color is detected, the system starts the painting operation. Moreover, the system has the capability to automatically cleaning the spray gun and the connected tubes in the case of having the successive objects to be painted in different colors. 

References

  • A. Ata, A. Eleyan, Innovative Painting Robotic Cell for Industrial Applications, 3rd International Symposium on Innovative Technologies in Engineering and Science (ISITES2015), Valencia, Spain, June 2015.
  • A. Ata, A. Eleyan, An Autonomous Robotic Cell for Painting Applications, Proceedings of the IASTED In-ternational Conference Modelling, Identification and Control (MIC 2017), pp. 200-207, Innsbruck, Austria, February 2017.
  • A. Gasparetto, R. Vidoni, D. Pillan and E. Saccavini, “Automatic Path and Trajectory Planning for Robotic Spray Painting”, 7th German Conference on Robotics, pp. 5925 - 5930, May 2012
  • Z. Bo, F. Fang, S. Zhenhua, M. Zhengda and D. Xian-zhong, “Fast and Template Path Planning of Spray Painting Robots for Regular Surfaces”, 34th Chinese Control Conference (CCC), pp. 211- 216, July 2015
  • J. MU and Y. Li, “A New Efficient Real-Time Arbitrary Colored Ball Recognition Method for A Humanoid Soccer Robot”, 12th World Congress on Intelligent Control and Automation (WCICA), pp. 494 - 499, Sept 2016
  • K. J. Shin, “Detecting the Position of The Fish Robot Using the Color Segment Algorithm”, Future Technol-ogies Conference (FTC), pp. 896 - 900, Dec. 2016
  • R. Szabo, A. Gontean and A. Sfirat, “Robotic Arm Control in Space with Color Recognition Using a Raspberry Pi”, 39th International Conference on Tele-communications and Signal Processing (TSP), pp. 689 – 692, Dec. 2016
  • A.S Silva, F. Marcolino Q. Severgnini and M. L. Oliveira, “Object tracking by color and active contour model s segmentation”, IEEE Latin America Transac-tions, pp. 1488 - 1493, April 2016
  • M. Russell and S. Fischaber, “OpenCV Based Road Sign Recognition on Zynq”, 11th IEEE International Conference on Industrial Informatics (INDIN), pp. 596 - 601, July 2013
  • P. Constante, A. Gordon and O. Chang, “Artificial vision techniques for strawberry’s industrial classifica-tion”, IEEE Latin America Transactions, pp. 2576 - 2581, Aug. 2016
Year 2018, Volume: 14 Issue: 1, 17 - 22, 30.03.2018
https://doi.org/10.18466/cbayarfbe.306950

Abstract

References

  • A. Ata, A. Eleyan, Innovative Painting Robotic Cell for Industrial Applications, 3rd International Symposium on Innovative Technologies in Engineering and Science (ISITES2015), Valencia, Spain, June 2015.
  • A. Ata, A. Eleyan, An Autonomous Robotic Cell for Painting Applications, Proceedings of the IASTED In-ternational Conference Modelling, Identification and Control (MIC 2017), pp. 200-207, Innsbruck, Austria, February 2017.
  • A. Gasparetto, R. Vidoni, D. Pillan and E. Saccavini, “Automatic Path and Trajectory Planning for Robotic Spray Painting”, 7th German Conference on Robotics, pp. 5925 - 5930, May 2012
  • Z. Bo, F. Fang, S. Zhenhua, M. Zhengda and D. Xian-zhong, “Fast and Template Path Planning of Spray Painting Robots for Regular Surfaces”, 34th Chinese Control Conference (CCC), pp. 211- 216, July 2015
  • J. MU and Y. Li, “A New Efficient Real-Time Arbitrary Colored Ball Recognition Method for A Humanoid Soccer Robot”, 12th World Congress on Intelligent Control and Automation (WCICA), pp. 494 - 499, Sept 2016
  • K. J. Shin, “Detecting the Position of The Fish Robot Using the Color Segment Algorithm”, Future Technol-ogies Conference (FTC), pp. 896 - 900, Dec. 2016
  • R. Szabo, A. Gontean and A. Sfirat, “Robotic Arm Control in Space with Color Recognition Using a Raspberry Pi”, 39th International Conference on Tele-communications and Signal Processing (TSP), pp. 689 – 692, Dec. 2016
  • A.S Silva, F. Marcolino Q. Severgnini and M. L. Oliveira, “Object tracking by color and active contour model s segmentation”, IEEE Latin America Transac-tions, pp. 1488 - 1493, April 2016
  • M. Russell and S. Fischaber, “OpenCV Based Road Sign Recognition on Zynq”, 11th IEEE International Conference on Industrial Informatics (INDIN), pp. 596 - 601, July 2013
  • P. Constante, A. Gordon and O. Chang, “Artificial vision techniques for strawberry’s industrial classifica-tion”, IEEE Latin America Transactions, pp. 2576 - 2581, Aug. 2016
There are 10 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

İbrahim Kesici This is me

Şeyma Bişkin This is me

Alaa Eleyan

Publication Date March 30, 2018
Published in Issue Year 2018 Volume: 14 Issue: 1

Cite

APA Kesici, İ., Bişkin, Ş., & Eleyan, A. (2018). Automatic Object Painting with SCARA Robot Using Computer Vision. Celal Bayar University Journal of Science, 14(1), 17-22. https://doi.org/10.18466/cbayarfbe.306950
AMA Kesici İ, Bişkin Ş, Eleyan A. Automatic Object Painting with SCARA Robot Using Computer Vision. CBUJOS. March 2018;14(1):17-22. doi:10.18466/cbayarfbe.306950
Chicago Kesici, İbrahim, Şeyma Bişkin, and Alaa Eleyan. “Automatic Object Painting With SCARA Robot Using Computer Vision”. Celal Bayar University Journal of Science 14, no. 1 (March 2018): 17-22. https://doi.org/10.18466/cbayarfbe.306950.
EndNote Kesici İ, Bişkin Ş, Eleyan A (March 1, 2018) Automatic Object Painting with SCARA Robot Using Computer Vision. Celal Bayar University Journal of Science 14 1 17–22.
IEEE İ. Kesici, Ş. Bişkin, and A. Eleyan, “Automatic Object Painting with SCARA Robot Using Computer Vision”, CBUJOS, vol. 14, no. 1, pp. 17–22, 2018, doi: 10.18466/cbayarfbe.306950.
ISNAD Kesici, İbrahim et al. “Automatic Object Painting With SCARA Robot Using Computer Vision”. Celal Bayar University Journal of Science 14/1 (March 2018), 17-22. https://doi.org/10.18466/cbayarfbe.306950.
JAMA Kesici İ, Bişkin Ş, Eleyan A. Automatic Object Painting with SCARA Robot Using Computer Vision. CBUJOS. 2018;14:17–22.
MLA Kesici, İbrahim et al. “Automatic Object Painting With SCARA Robot Using Computer Vision”. Celal Bayar University Journal of Science, vol. 14, no. 1, 2018, pp. 17-22, doi:10.18466/cbayarfbe.306950.
Vancouver Kesici İ, Bişkin Ş, Eleyan A. Automatic Object Painting with SCARA Robot Using Computer Vision. CBUJOS. 2018;14(1):17-22.