CAD应该用什么形状语法:14例形状嵌入

IF 1.7 3区工程技术 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Ai Edam-Artificial Intelligence for Engineering Design Analysis and Manufacturing Pub Date : 2022-02-09 DOI:10.1017/S0890060421000263

T. Hong, A. Economou

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引用次数: 2

摘要

基于给定欧氏变换、仿射变换或线性变换下形状嵌入的形状查询在当前CAD系统中是不存在的。唯一尝试实现形状嵌入的系统是形状语法解释器，尽管有希望但结果不确定。这里的工作根据可用配准点的数量确定了所有可能的14种形状嵌入情况，其中4种用于确定情况，10种用于不确定情况，并概述了一种方法来处理不确定情况下的复杂性。所有的视觉计算都是由欧几里得平面上的直线组成的形状完成的，在代数Uij中，i = 1是直线的维度，j = 2是定义、变换和组合直线的空间维度。界面设计和集成到当前工作设计工作流的方面被故意搁置一边。

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What shape grammars do that CAD should: the 14 cases of shape embedding

Abstract Shape queries based on shape embedding under a given Euclidean, affine, or linear transformation are absent from current CAD systems. The only systems that have attempted to implement shape embedding are the shape grammar interpreters albeit with promising but inconclusive results. The work here identifies all possible 14 cases of shape embedding with respect to the number of available registration points, four for determinate cases and ten for indeterminate ones, and an approach is sketched to take on the complexities underlying the indeterminate cases. All visual calculations are done with shapes consisting of straight lines in the Euclidean plane within the algebra Uij for i = 1 the dimension of lines and j = 2 the dimension of space in which the lines are defined, transformed and combined. Aspects of interface design and integration to current work design workflows are deliberately left aside.

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来源期刊

Ai Edam-Artificial Intelligence for Engineering Design Analysis and Manufacturing 工程技术-工程：制造

CiteScore

4.40

自引率

14.30%

发文量

审稿时长

>12 weeks

期刊介绍： The journal publishes original articles about significant AI theory and applications based on the most up-to-date research in all branches and phases of engineering. Suitable topics include: analysis and evaluation; selection; configuration and design; manufacturing and assembly; and concurrent engineering. Specifically, the journal is interested in the use of AI in planning, design, analysis, simulation, qualitative reasoning, spatial reasoning and graphics, manufacturing, assembly, process planning, scheduling, numerical analysis, optimization, distributed systems, multi-agent applications, cooperation, cognitive modeling, learning and creativity. AI EDAM is also interested in original, major applications of state-of-the-art knowledge-based techniques to important engineering problems.