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Point cloud modeling and slicing algorithm for trajectory planning of spray painting robot

Published online by Cambridge University Press:  29 June 2021

Xinyi Yu ,
Zhaoying Cheng Open the ORCID record for Zhaoying Cheng [Opens in a new window] ,
Yikai Zhang  and
Linlin Ou
Xinyi Yu
Affiliation:
Department of Automation, Zhejiang University of Technology, Hangzhou, China
Zhaoying Cheng
Affiliation:
Department of Automation, Zhejiang University of Technology, Hangzhou, China
Yikai Zhang
Affiliation:
Department of Automation, Zhejiang University of Technology, Hangzhou, China
Linlin Ou*
Affiliation:
Department of Automation, Zhejiang University of Technology, Hangzhou, China
*
*Corresponding author. Email: linlinou@zjut.edu.cn
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Abstract

To improve the uniformity of coating thickness and spraying efficiency, new point cloud modeling and slicing algorithm are proposed to deal with free-form surfaces for the spray painting robot in this paper. In the process of point cloud modeling, the edge preservation algorithm is firstly presented to avoid damaging the edge characteristic of the point cloud model. For the spraying gun, the coating deposition model on the free-form surface is determined on the basis of the elliptic double β distribution model. Then, the grid projection algorithm is proposed to obtain grid points between adjacent slices on the free-form surface. Based on this, the analytical solution for calculating the coating thickness at each grid point is obtained. The cross-section contour points are obtained by intercepting the point cloud model with several parallel slices, which is important for the trajectory planning of the spray painting robot. Finally, the uniformity of coating thickness is optimized in terms of the moving speed of the spraying gun and the slice thickness. The simulation and numerical experiment results show that the uniformity of coating thickness and spraying efficiency are improved using the proposed point cloud modeling and slicing algorithm.

Keywords

edge preservationcoating deposition modelpoint cloud slicinggrid projection
Type
Article
Information
Robotica , Volume 39 , Issue 12 , December 2021 , pp. 2246 - 2267
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

Chen, H. P., Sheng, W. H., Xi, N., Song, M. M. and Chen, Y. F., “Automated Robot Trajectory Planning for Spray Painting of Free-Form Surfaces in Automotive Manufacturing,” Proceedings 2002 IEEE International Conference on Robotics and Automation 1(1), 450–455 (2002).Google Scholar
Bouraine, S. and Azouaoui, O., “Safe motion planning based on a new encoding technique for tree expansion using particle swarm optimization,” Robotica 39(5), 1–43 (2020).Google Scholar
Xia, J., Jiang, Z. N. and Zhang, T., “Feasible arm configurations and its application for human-like motion control of SRS-redundant manipulators with multiple constraints,” Robotica 39(6), 1–17 (2020).Google Scholar
Wang, T., Xue, Z., Dong, X. and Xie, S., “Autonomous intelligent planning method for welding path of complex ship components,” Robotica 39(3), 428–437 (2021).10.1017/S0263574720000454CrossRefGoogle Scholar
Chen, H. P., Xi, N., “Automated robot tool trajectory connection for spray forming process,” J. Manuf. Sci. Eng. 134(2), 171–179 (2012).10.1115/1.4005798CrossRefGoogle Scholar
Antonio, J. K. and Ramabhadran, R. L., “A framework for trajectory planning for automated spray coating,” Int. J. Rob. Autom. 12(4), 124–134 (1997).Google Scholar
Chen, H. P. and Sheng, W. H., “Transformative Industrial Robot Programming in Surface Manufacturing,” IEEE International Conference on Robots and Automation (2011) pp. 6059–6064.Google Scholar
Chen, H. P. and Xi, N., “Journal of manufacturing science and engineering,” J. Manuf. Sci. Eng. 134(2), 171–179 (2012).Google Scholar
Zeng, Y., Gong, J. and Xu, N., “Tool trajectory optimization of spray painting robot for many-times spray painting,” Int. J. Control Autom. 7(8), 193–208 (2014).10.14257/ijca.2014.7.8.17CrossRefGoogle Scholar
Li, X., Landsnes, O. A., Chen, H., “Automatic Trajectory Generation for Robotic Painting Application,” ISR 2010 (41st International Symposium on Robotics) and ROBOTIK 2010 (6th German Conference on Robotics) (2010) pp. 1–6.Google Scholar
Tang, Y. and Chen, W., “Surface modeling of workpiece and tool trajectory planning for spray painting robot,” Plos One 10(5), 127–139 (2015).Google ScholarPubMed
Chen, W. and Liu, J., “Automatic spray trajectory optimization on BÉzier surface,” Electronics 8(2), 168 (2019).10.3390/electronics8020168CrossRefGoogle Scholar
Arika, M. A. S., “Process modeling, simulation, and paint thickness measurement for robotic spray painting,” J. Rob. Syst. 17(9), 479–494 (2000).Google Scholar
Chen, H. P. and Xi, N.. “Automated tool trajectory planning of industrial robots for painting composite surfaces,” Int. J. Adv. Manuf. Technol. 35, 680–696 (2008).CrossRefGoogle Scholar
Wang, G., Cheng, J. and Li, R., “A New Point Cloud Slicing Based on Path Planning Algorithm for Robotic Spray Painting,” 2015 IEEE International Conference on Robotics and Biomimetics (2015), pp. 1717–1722.Google Scholar
Gleeson, D., Jakobsson, S., Salman, R., Sandgren, N., Edelvik, F., Carlson, J. S. and Lennartson, B., “Robot Spray Painting Trajectory Optimization,” 2020 IEEE 16th International Conference on Automation Science and Engineering (2020) pp. 1135–1140.Google Scholar
Choubey, C. and Ohri, J., “Optimal trajectory generation for a 6-DOF parallel manipulator using grey wolf optimization algorithm,” Robotica 39(3), 411–427 (2021).10.1017/S0263574720000442CrossRefGoogle Scholar
Suh, S. H., Woo, I. K. and Noh, S. K., “Development of an Automatic Trajectory Planning System (ATPS) for Spray Painting Robots,” Proceedings. 1991 IEEE International Conference on Robotics and Automation (1991) pp. 1948–1955.Google Scholar
Li, F., “Trajectory optimization of spray painting robot based on CAD,” Trans. Chin. Soc. Agri. 41(5), 213–217 (2010).Google Scholar
Gong, D., “Trajectory optimization of spray painting robot for natural quadric surfaces,” China Mech. Eng. 22(3), 282–290 (2011).Google Scholar
Zhang, Y. K., “Planning method of offset spray path for patch considering boundary factors,” Math. Problems Eng. 2018(1), 1–7 (2018).Google Scholar
Chen, H. P. and Fuhlbrigge, T., “Automated Industrial Robot Path Planning for Spray Painting Process: A Review,” 4th IEEE Conference on Automation Science and Engineering (2008) pp. 522–527.Google Scholar
Kout, A. and Muller, H., “Tool-adaptive offset path on triangular mesh workpiece surfaces,” Comput. Aided Des. 50(13), 61–73 (2007).CrossRefGoogle Scholar
Guan, L. and Chen, L., “Trajectory planning method based on transitional segment optimization of spray painting robot on complex-free surface,” Ind. Robot Int. J. Rob. Res. Appl. 46(1), 31–43 (2019).10.1108/IR-02-2018-0033CrossRefGoogle Scholar
He, G. and Yang, J., “Application of the slicing technique to extract the contour feature line,” Cluster Comput. 22(6), 13937–13943 (2019).10.1007/s10586-018-2144-9CrossRefGoogle Scholar
Zolanvari, S. M. I and Laefer, D. F., “Slicing method for curved faÇade and window extraction from point clouds,” ISPRS J. Photogramm. Remote Sens. 119(13), 334–346 (2016).10.1016/j.isprsjprs.2016.06.011CrossRefGoogle Scholar
Kokab, H. S. and Urbanic, R. J., “Extracting of cross section profiles from complex point cloud data sets,” IFAC-PapersOnLine 52(10), 346–351 (2019).10.1016/j.ifacol.2019.10.055CrossRefGoogle Scholar
Fan, J., Ma, L. and Sun, A., “An approach for extracting curve profiles based on scanned point cloud,” Measurement 149(6), 107–123 (2020).10.1016/j.measurement.2019.107023CrossRefGoogle Scholar
Li, M. Z., Lu, Z. P. and Sha, C. F., “Trajectory generation of spray painting robot using point cloud slicing,” Appl. Mech. Mater. 44(6), 1290–1294 (2011).Google Scholar
Chen, W., Li, X. and Ge, H., “Trajectory planning for spray painting robot based on point cloud slicing technique,” Electronics 9(6), 908 (2020).10.3390/electronics9060908CrossRefGoogle Scholar
Tong, N., Kong, M. and Xu, S., “A Spray Path Planning Algorithm Based on 3D Point Cloud,” 2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (2019) pp. 1112–1117.Google Scholar
Liu, C. J., Jian, L., Zhang, S. F., “A point clouds filtering algorithm based on grid partition and moving least squares,” Procedia Eng. 28(3), 476–482 (2012).Google Scholar
Balkan, T. and M. A. S Arikan, “Modeling of paint flow rate flux for circular paint sprays by using experimental paint thickness distribution,” Mech. Res. Commun. 26(1), 609–617 (2006).CrossRefGoogle Scholar
Arikan, M. A. S and Balkan, T., “Process modeling, simulation, and paint thickness measurement for robotic spray painting,” J. Rob. Syst. 17(9), 479–494 (2000).10.1002/1097-4563(200009)17:9<479::AID-ROB3>3.0.CO;2-L3.0.CO;2-L>CrossRefGoogle Scholar
Zhang, J., Cao, J. and Liu, X., “Point cloud normal estimation via low-rank subspace clustering,” Comput. Graph. 37(6), 697–706 (2013).10.1016/j.cag.2013.05.008CrossRefGoogle Scholar
Rao, S. S., Optimization: Theory and Application (John Wiley & Sons, Inc., New York, 1983).Google Scholar