论文标题
Sketchopt：基于草图的参数模型检索生成设计
SketchOpt: Sketch-based Parametric Model Retrieval for Generative Design
论文作者
论文摘要
为基于绩效的生成设计任务开发完全参数的建筑模型通常需要在许多高级3D建模和视觉编程中熟练，从而限制了其用于许多建筑设计师的使用。此外，此类模型的迭代可能是耗时的任务，有时是限制的，因为布局设计的重大变化可能会导致整个参数定义进行重塑。为了应对这些挑战，我们引入了一种新型的自动化生成设计系统，该系统将基本的平面图作为输入，并提供了一个用于多目标建筑优化作为输出的参数模型。此外，用户设计器可以通过使用图纸中的简单注释来为其所需的构建元素分配各种设计变量。该系统将识别相应的元素并定义可变约束，以准备多个目标优化问题。
Developing fully parametric building models for performance-based generative design tasks often requires proficiency in many advanced 3D modeling and visual programming, limiting its use for many building designers. Moreover, iterations of such models can be time-consuming tasks and sometimes limiting, as major changes in the layout design may result in remodeling the entire parametric definition. To address these challenges, we introduce a novel automated generative design system, which takes a basic floor plan sketch as an input and provides a parametric model prepared for multi-objective building optimization as output. Furthermore, the user-designer can assign various design variables for its desired building elements by using simple annotations in the drawing. The system would recognize the corresponding element and define variable constraints to prepare for a multi-objective optimization problem.
