Paint deposition modeling for trajectory planning on automotive surfaces

被引:82
作者
Conner, DC [1 ]
Greenfield, A
Atkar, PN
Rizzi, AA
Choset, H
机构
[1] Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA
[2] Carnegie Mellon Univ, Dept Mech Engn, Pittsburgh, PA 15213 USA
基金
美国国家科学基金会;
关键词
automotive painting; trajectory planning; coverage;
D O I
10.1109/TASE.2005.851631
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This research is focused on developing trajectory planning tools for the automotive painting industry. The geometric complexity of automotive surfaces and the complexity of the spray patterns produced by modern paint atomizers combine to make this a challenging and interesting problem. This paper documents our efforts to develop computationally tractable analytic deposition models for electrostatic rotating bell (ESRB) atomizers,which have recently become widely used in the automotive painting industry. The models Presented in this paper account for both the effects of surface curvature as well as the deposition pattern of ESRB atomizers in a computationally tractable form, enabling the development of automated trajectory generation tools. We present experimental results used to develop and validate the models, and verify the interaction between the deposition pattern, the atomizer trajectory, and the surface curvature. Limitations of the deposition model with respect to predictions of paint deposition on highly curved surfaces are discussed.
引用
收藏
页码:381 / 392
页数:12
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