A Trajectory Generation Method Based on Edge Detection for Auto-Sealant Cartesian Robot

Eka Samsul Maarif, Endra Pitowarno, Rusminto Tjatur Widodo


This paper presents algorithm ingenerating trajectory for sealant process using captured image. Cartesian robot as auto-sealant in manufacturing process has increased productivity, reduces human error and saves time. But, different sealant path in many engine models means not only different trajectory but also different program. Therefore robot with detection ability to generate its own trajectory is needed. This paper describes best lighting technique in capturing image and applies edge detection in trajectory generation as the solution. The algorithm comprises image capturing, Canny edge detection, integral projection in localizing outer most edge, scanning coordinates, and generating vector direction codes. The experiment results show that the best technique is diffuse lighting at 10 Cd. The developed method gives connected point to point trajectory which forms sealant path with a point to next point distance is equal to 90° motor rotation. Directional movement for point to point trajectory is controlled by generated codes which are ready to be sent by serial communication to robot controller as instruction for motors which actuate axes X and Y directions.


canny edge detection; integral projection; scanning the coordinate; vector direction code

Full Text:



Y. Maddahi, "Reliability and Quality Improvement of Robotic Manipulation Systems," WSEAS Transactions on Systems and Control, vol. Volume 6, pp. 339-348, 2011.

S. Brell-Cokcan, "A New Parametric Design Tool for Robot Milling," ACADIA, 2010.

E. Pitowarno, et al.,"Knowledge-Based Trajectory Error Pattern Method Applied To An Active Force Control Scheme," IIUM Engineering Journal, vol. 3 No.1, 2002.

B. Takarics and P. T. Szemes,"Super flexible Welding Robot Based on the Intelligent Space Concept," presented at the 7th International Symposium of Hungarian Researchers on Computational Intelligence, 2008.

B. Kuljic, "Path finding Based on Edge Detection and Infrared Distance Measuring Sensor," Acta Polytechnica Hungarica, vol. 6 No.1, pp. 103-116, 2009.

M. Mirdanies, et al., "Object Recognition System In Remote Controlled Weapon Station Using Sift And Surf Methods," Journal of Mechatronics, Electrical Power and Vehicular Technology, vol. 04, No. 2, pp. 99-108, 2013. crossref

E. S. Maarif, "Applied Canny Edge Detection in Trajectory Planning for Auto-Sealant Cartesian Robot," in Indonesian Symposium on Robot Soccer Competition 2013, Semarang, Indonesia, 2013.

E. Nadernejad, "Edge Detection Techniques: Evaluations and Comparisons," Applied Mathematical Sciences, vol. 2, No. 31, pp. 1507 – 1520, 2008.

P. Kalra. “Canny Edge Detection,?. Lecturer Classroom. Department of Computer Science and Engineering. India Institute of Technology, New Delhi. 2009. [Online]. Available: www.cse.iitd.ernet.in/~pkalra/csl783/canny.pdf

Y. Surya, "Machine Vision Implementation in Rapid PCB Prototyping," Journal of Mechatronics, Electrical Power, and Vehicular Technology, vol. 02, No. 2, pp. 79-84, 2011.crossref

S. Dutta and B. B. Chaudhuri, "A Color Edge Detection Algorithm in RGB Color Space," in International Conference on Advances in Recent Technologies in Communication and Computing., 2009, pp. 337-340.crossref

M. Juneja and P. S. Sandhu, "Performance Evaluation of Edge Detection Techniques for Images in Spatial Domain," International Journal of Computer Theory. crossref

G. T. Shrivakshan and C. Chandrasekar, "A Comparison of various Edge Detection Techniques used in Image Processing," International Journal of Computer Science Issues (IJCSI), vol. Vol. 9, Issue 5, No. 1, pp. 269 -276, September 2012.

P. Zhou, "An Improved Canny Algorithm for Edge Detection," Journal of Computation Information Systems, pp. 1516-1523, 2011.

G. J. Mohammed, "Eyeball Localization Based on Angular Integral Projection Function," Slovenian Society Informatica, vol. 33 Issue 4, pp. 475-480, November 2009.

S. P. Khandait, et al., "Comparative Analysis of ANFIS and NN Approach for Expression Recognition using Geometry Method," International Journal of Advanced Research in Computer Science and Software Engineering, vol. 2, Issue 3, March 2012.

L. Xiao-Yan and C. Yan-Li, "Application of Dijkstra Algorithm in Logistics Distribution Lines," in Third International Symposium on Computer Science and Computational Technology (ISCSCT ’10), Jiaozuo, P. R. China, August, 2010, pp. 048-050.

Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM


  • There are currently no refbacks.

Copyright (c)