Abstract
To make robotic welding systems more flexible, vision sensors are introduced as they provide large amount of information about the welding components. In this paper a method is introduced to automatically locate the weld seam between two objects in butt welding applications. The proposed method provides flexibility for robotic welding by having the ability to locate the weld seam on arbitrarily positioned work pieces. This method is also cost effective as it is developed using images captured from a low cost web-cam. Furthermore, the proposed method is able to plan a robot path along the identified seam. Simulation and experimental results show that the method can be used successfully in detecting and locating seams on variously shaped work pieces and robot paths can be successfully generated to follow the weld seams.
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References
Chen, S., Zhang, Qiu, T., Lin, T.: Robotic Welding Systems with Vision-Sensing and Self- Learning Neuron Control of Arc Welding Dynamic Process. Journal of Intelligent Robotic Systems 36, 191–208 (2003)
Corke, P.: Visual Control of Robots: High Performance Visual Servoing. Research Study Press, Somerset (1996)
Cook, G.: Feedback Control of Process Variables in Arc Welding. In: Proceedings of IEEE Joint Automatic Control Conference, vol. 2 (1980)
Dinham, M., Fang, G.: Low Cost Eye in Hand Camera Calibration. In: Proceedings of The 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO 2009), Guilin, Guangxi, China, December 18-22, pp. 1889–1893 (2009)
Dudek, G., Jenkin, M.: Computational Principles of Mobile Robotics. Cambridge University Press, New York (2000)
Gao, S., Zhao, M., Zhang, L., Zou, Y.: Dual-Beam Structured Light Vision System for 3D Coordinates Measurment. In: Proceedigns of the 7th Annual Conference, World Congress on Intelligent Control Automation, Chongqing, China (2008)
Lee, J., Sun, Y., Chen, C.: Multiscale Corner Detection by using Wavelet Transform. IEEE Transactions on Image Processing 4(1), 100–104 (1995)
Li, L., Chen, W.: Corner Detection Interprestation on Planar Curves using Fuzzy Logic Reasoning. IEEE Transactions on Image Processing 2(11), 1024–1210 (1999)
Liu, X., Wang, G., Shi, Y.: Image Processing of Welding Seam Based on Single-Stripe Laser Vision Systems. In: Sixth International Conference, Conference on Intelligent Systems Design and Applications (2006)
Rattarangsi, A., Chin, R.: Scale-Based Detection of Corners of Planar Curves. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(4), 430–449 (1992)
Rosenfeld, A., Johnson, E.: Angle Detection on Digital Curves. IEEE Transactions on Computers 22, 875–878 (1973)
Shen, H., Lin, T., Chen, S.: A Study on Vision-Based Real-Time Seam Tracking in Robotic Arc Welding. Robot. Weld Intelligence. & Automation, 311–318 (2007)
Shi, F., Zhou, L., Lin, T., Chen, S.: Efficient Weld Seam Detection for Robotic Welding from a Single Image. Robot. Weld Intelligence. & Automation, 289–294 (2007)
Sicard, P., Levine, M.: An Approach to an Expert Robot Welding System. IEEE Transactions on Systems, Man and Cybernetics 18(2), 204–213 (1988)
Sun, T.: K-Cosine Corner Detection. Journal of Computers 3(7), 16–22 (2008)
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© 2011 Springer-Verlag Berlin Heidelberg
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Micallef, K., Fang, G., Dinham, M. (2011). Automatic Seam Detection and Path Planning in Robotic Welding. In: Tarn, TJ., Chen, SB., Fang, G. (eds) Robotic Welding, Intelligence and Automation. Lecture Notes in Electrical Engineering, vol 88. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19959-2_3
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DOI: https://doi.org/10.1007/978-3-642-19959-2_3
Publisher Name: Springer, Berlin, Heidelberg
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