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A Comparison of verified distance computation between implicit objects using different arithmetics for range enclosure

机译:使用距离范围封闭的不同算法对隐式对象之间经过验证的距离计算进行比较

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This paper describes a new algorithm for computing verified bounds on the distance between two arbitrary fat implicit objects. The algorithm dissects the objects into axis-aligned boxes by constructing an adaptive hierarchical decomposition during runtime. Actual distance computation is performed on the cubes independently of the original object's complexity. As the whole decomposition process and the distance computation are carried out using verified techniques like interval arithmetic, the calculated bounds are rigorous. In the second part of the paper, we test our algorithm using 18 different test cases, split up into 5 groups. Each group represents a different level of complexity, ranging from simple surfaces like the sphere to more complex surfaces like the Kleins bottle. The algorithm is independent of the actual technique for range bounding, which allows us to compare different verified arithmetics. Using our newly developed uniform framework for verified computations, we perform tests with interval arithmetic, centered forms, affine arithmetic and Taylor models. Finally, we compare them based on the time needed for deriving verified bounds with a user defined accuracy.
机译:本文介绍了一种新算法,用于计算两个任意胖隐式对象之间的距离的已验证范围。该算法通过在运行时构造自适应分层分解,将对象分解为轴对齐的框。实际距离计算是在多维数据集上执行的,与原始对象的复杂性无关。由于整个分解过程和距离计算均使用间隔算术等经过验证的技术进行,因此计算出的边界非常严格。在本文的第二部分中,我们使用18个不同的测试案例(分为5组)测试了我们的算法。每个组代表不同级别的复杂性,范围从简单的表面(例如球体)到更复杂的表面(例如Kleins瓶)。该算法与范围限制的实际技术无关,这使我们可以比较不同的经过验证的算法。使用我们新开发的统一框架进行验证计算,我们使用区间算术,居中形式,仿射算术和泰勒模型执行测试。最后,我们根据用户定义的精度得出验证边界所需的时间对它们进行比较。

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