Paint Deposition Modeling for Trajectory Planning on Automotive Surfaces

David C. Conner, Aaron L. Greenfield, Prasad Atkar, Alfred Rizzi and Howie Choset
Journal Article, Carnegie Mellon University, IEEE Transactions on Automation Science and Engineering, Vol. 2, No. 4, pp. 381 - 392, October, 2005

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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 deposi- tion 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.

author = {David C. Conner and Aaron L. Greenfield and Prasad Atkar and Alfred Rizzi and Howie Choset},
title = {Paint Deposition Modeling for Trajectory Planning on Automotive Surfaces},
journal = {IEEE Transactions on Automation Science and Engineering},
year = {2005},
month = {October},
volume = {2},
number = {4},
pages = {381 - 392},
} 2017-09-13T10:43:07-04:00