Deposition Modeling for Paint Application on Surfaces Embedded in R^3

David C. Conner, Prasad Atkar, Alfred Rizzi and Howie Choset
Tech. Report, CMU-RI-TR-02-08, Robotics Institute, Carnegie Mellon University, October, 2002

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As part of an ongoing collaborative effort with the Ford Motor Company, our research aims to develop practical and efficient trajectory planning tools for automotive painting. Not only must the paint applicator pass over all points on the surface, it must do so in a manner that ensures the uniformity of the coating thickness. This is non-trivial given the complexity of automotive surfaces. This report documents our efforts to develop analytic deposition models for electrostatic rotating bell (ESRB) atomizers, which have recently become widely used in the automotive painting industry. Conventional deposition models, used in earlier automatic trajectory planning tools, fail to capture the complexity of deposition patterns generated by ESRB atomizers. The models presented here take into account both the surface curvature and the deposition pattern of ESRB atomizers, enabling planning tools to optimize atomizer trajectories to meet several measures of quality, such as coating uniformity. In addition to the development of our models, we present experimental results used to evaluate our models, and verify the interaction between the deposition pattern, trajectory, and surface curvature.

author = {David C. Conner and Prasad Atkar and Alfred Rizzi and Howie Choset},
title = {Deposition Modeling for Paint Application on Surfaces Embedded in R^3},
year = {2002},
month = {October},
institution = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-RI-TR-02-08},
keywords = {Automotive Painting, Trajectory Planning, Deposition Modeling},
} 2017-09-13T10:44:58-04:00