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喷漆机器人的工件表面建模与刀具轨迹规划

Surface modeling of workpiece and tool trajectory planning for spray painting robot.

作者信息

Tang Yang, Chen Wei

机构信息

School of Science, Jiangsu University, Zhenjiang, China.

School of Electronics and Information,Jiangsu University of Science and Technology, Zhenjiang, China.

出版信息

PLoS One. 2015 May 18;10(5):e0127139. doi: 10.1371/journal.pone.0127139. eCollection 2015.

DOI:10.1371/journal.pone.0127139
PMID:25993663
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4436337/
Abstract

Automated tool trajectory planning for spray-painting robots is still a challenging problem, especially for a large free-form surface. A grid approximation of a free-form surface is adopted in CAD modeling in this paper. A free-form surface model is approximated by a set of flat patches. We describe here an efficient and flexible tool trajectory optimization scheme using T-Bézier curves calculated in a new way from trigonometrical bases. The distance between the spray gun and the free-form surface along the normal vector is varied. Automotive body parts, which are large free-form surfaces, are used to test the scheme. The experimental results show that the trajectory planning algorithm achieves satisfactory performance. This algorithm can also be extended to other applications.

摘要

喷漆机器人的自动工具轨迹规划仍然是一个具有挑战性的问题,特别是对于大型自由曲面。本文在CAD建模中采用了自由曲面的网格近似方法。自由曲面模型由一组平面片近似表示。我们在此描述一种高效且灵活的工具轨迹优化方案,该方案使用从三角基以新方式计算的T - 贝塞尔曲线。喷枪与自由曲面沿法向量的距离是可变的。以汽车车身部件这种大型自由曲面为例对该方案进行测试。实验结果表明,轨迹规划算法具有令人满意的性能。该算法还可扩展到其他应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/fd5530632a3a/pone.0127139.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/ba6a31dec3c2/pone.0127139.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/9c7b259d89d8/pone.0127139.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/9c90661f2e63/pone.0127139.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/c8aa129f3e3e/pone.0127139.g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/fd5530632a3a/pone.0127139.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/ba6a31dec3c2/pone.0127139.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/9c7b259d89d8/pone.0127139.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/9c90661f2e63/pone.0127139.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/c8aa129f3e3e/pone.0127139.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/d7218a108315/pone.0127139.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06d0/4436337/fd5530632a3a/pone.0127139.g006.jpg

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