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Uniform Coverage of Simple Surfaces Embedded in for Auto-Body Painting

机译:嵌入式用于自动绘画的简单表面覆盖

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We develop a procedure for automated trajectory generation for robotic spray painting applications. Painting requires that the spray gun deposit paint at each point on the target surface such that the variation of the resultant paint deposition is within acceptable limits; we term this the uniform coverage problem. To understand the key issues in the uniform coverage problem, we consider surface patches that are geodesically convex and topologically simple to represent realistic automotive surfaces. Our goal is to understand the relationship between the spray gun trajectory and the following output characteristics: deposition uniformity, cycle time, and paint waste. Our planning approach decomposes the coverage trajectory generation problem into three subproblems: selection of the start curve, selection of the speed pro.les along each pass, and selection of the spacing between the passes. Using concepts such as area magni.cation, the Gauss-Bonnet theorem from differential geometry, and standard optimization procedures, we present procedures to solve each subproblem independently of the others. Finally, we demonstrate our trajectory planning procedures in simulation as well as experimentally on simple surfaces that approximate real automobile surfaces.
机译:我们开发了一种用于机器人喷涂应用的自动轨迹生成的程序。绘画要求在目标表面上的每个点处喷射枪沉积涂料,使得所得涂料沉积的变化在可接受的限度范围内;我们术语这个统一的覆盖问题。要了解统一覆盖问题中的关键问题,我们考虑了几个凸起的曲面斑块,拓扑易于代表现实的汽车表面。我们的目标是了解喷枪轨迹与以下输出特性之间的关系:沉积均匀性,循环时间和油漆废物。我们的规划方法将覆盖轨迹生成问题分解为三个子问题:选择开始曲线,沿着每次通过的速度Pro的选择,以及选择通过之间的间距。使用诸如区域Magni.cation等概念,来自差分几何的高斯通道定理以及标准优化程序,我们呈现用于独立于其他子问题解决每个子问题的程序。最后,我们展示了我们在模拟中的轨迹规划程序,以及实验上的简单表面,即近似真正的汽车表面。

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