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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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