Abstract
One of the highly skilled tasks in manufacturing is the polishing process. The purpose of polishing is to get uniform surface roughness. In order to reduce the polishing time and to cope with the shortage of skilled workers, robotic polishing technology has been investigated. This paper proposes a vision system to measure surface defects that have been classified to some level of surface roughness. Artificial neural networks are used to classify surface defects and to give a decision in order to drive the actuator of the arm robot. Force and rotation time have been chosen as output parameters of artificial neural networks. The results show that although there is a considerable change in both parameter values acquired from vision data compared to real data, it is still possible to obtain surface defects classification using a vision sensor to a certain limit of accuracy. The overall results of this research would encourage further developments in this area to achieve robust computer vision based surface measurement systems for industrial robotics, especially in the polishing process.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Liao, L., Xi, F., Liu, K.: Modeling and Control of Automated Polishing-Deburring Process using a Dual-Purpose Compliant Toolhead. Int. J. Machine Tools & Manufacture 48, 1454–1463 (2008)
Tam, H., Lui, O.C., Mok, A.C.K.: Robotic Polishing of Free Form Surfaces using Scanning Paths. J. Materials Processing Technology 95, 191–200 (1999)
Kuo, R.J.: Intelligent Robotic Die Polishing System Through Fuzzy Neural Networks and Multi-Sensor Fusion. In: Int. Joint Conf. on Neural Networks, pp. 2925–2928 (1993)
Besari, A.R.A., Palil, M.D.M., Zamri, R., Prabuwono, A.S.: A Review of Novel Sensing Techniques for Automatic Polishing Robot System. In: Nat. Conf. on Design and Concurrent Engineering, pp. 353–358 (2008)
Nagata, F., Kusumoto, Y., Fujimoto, Y., Watanabe, K.: Robotic Sanding System for New Designed Furniture with Free-Formed Surface. Robotics and Computer-Integrated Manufacturing 23, 371–379 (2007)
Zhao, J., Zhan, J., Jin, R., Tao, M.: An Oblique Ultrasonic Polishing Method by Robot for Free Form Surfaces. Int. J. Machine Tools & Manufacture 40, 795–808 (2000)
Yang, Z., Xi, F., Wu, B.: A Shape Adaptive Motion Control System with Application to Robotic Polishing. In: Robotics and Computer-Integrated Manufacturing, vol. 21, pp. 355–367 (2005)
Li, X., Wang, L., Cai, N.: Machine-Vision-Based Surface Finish Inspection for Cutting Tool Replacement in Production. Int. J. Production Research 42(11), 2279–2287 (2004)
Lee, B.Y., Yu, S.F., Juan, H.: The Model of Surface Roughness Inspection. Mechatronics 14, 129–141 (2004)
Kuo, R.J.: A Robotic Die Polishing System Through Fuzzy Neural Networks. Computers in Industry 32, 273–280 (1997)
Tong-Ying, G., Dao-Kui, Q., Zai-Li, D.: Research of Path Planning for Polishing Robot Based on Improved Genetic Algorithm. In: IEEE Int. Conf. on Robotics and Biomimetics, pp. 334–338 (2004)
Yang, Z., Chen, F., Zhao, J., Wu, X.: A Novel Vision Localization Method of Automated Micro-Polishing Robot. J. Bionic Engineering 6, 46–54 (2009)
Liu, Z., Zhao, J., Zhang, L., Chen, G., Li, D.: Realization of Mobile Robot Trajectory Tracking Control Based on Interpolation. In: IEEE Int. Symp. on Industrial Electronics, pp. 648–651 (2009)
Besari, A.R.A., Zamri, R., Rahman, K.A.A., Palil, M.D.M., Prabuwono, A.S.: Surface Defects Characterization in Polishing Process using Contour Dispersion. In: Int. Conf. on Soft Computing and Pattern Recognition, pp. 707–710 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Prabuwono, A.S., Besari, A.R.A., Zamri, R., Md Palil, M.D., Taufik (2011). Surface Defects Classification Using Artificial Neural Networks in Vision Based Polishing Robot. In: Jeschke, S., Liu, H., Schilberg, D. (eds) Intelligent Robotics and Applications. ICIRA 2011. Lecture Notes in Computer Science(), vol 7102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25489-5_58
Download citation
DOI: https://doi.org/10.1007/978-3-642-25489-5_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25488-8
Online ISBN: 978-3-642-25489-5
eBook Packages: Computer ScienceComputer Science (R0)