Generative Design workflows have introduced alternative paradigms in the domain of computational design, allowing designers to generate large pools of valid solutions by defining a set of goals and constraints. However, analyzing and narrowing down the generated solution space, which usually consists of various high-dimensional properties, has been a major challenge in current generative workflows. By taking advantage of the interactive unbounded spatial exploration, and the visual immersion offered in virtual reality platforms, we propose V-Dream, a virtual reality generative analysis framework for exploring large-scale solution spaces. V-Dream proposes a hybrid search workflow in which a spatial stochastic search approach is combined with a recommender system allowing users to pick desired candidates and eliminate the undesired ones iteratively. In each cycle, V-Dream reorganizes the remaining options in clusters based on the defined features. Moreover, our framework allows users to inspect design solutions and evaluate their performance metrics in various hierarchical levels, assisting them in narrowing down the solution space through iterative cycles of search/select/re-clustering of the solutions in an immersive fashion. Finally, we present a prototype of our proposed framework, illustrating how users can navigate and narrow down desired solutions from a pool of over 16000 monitor stands generated by Autodesk's Dreamcatcher software.

中文翻译：

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V-Dream：衍生式设计解决方案空间的沉浸式探索

生成式设计工作流在计算设计领域引入了替代范式，允许设计人员通过定义一组目标和约束来生成大量有效解决方案。然而，分析和缩小通常由各种高维属性组成的生成解决方案空间一直是当前生成工作流程中的主要挑战。通过利用交互式无界空间探索和虚拟现实平台提供的视觉沉浸，我们提出了 V-Dream，一种用于探索大规模解决方案空间的虚拟现实生成分析框架。V-Dream 提出了一种混合搜索工作流程，其中空间随机搜索方法与推荐系统相结合，允许用户选择所需的候选者并迭代地消除不需要的候选者。在每个循环中，V-Dream 根据定义的特征重新组织集群中的剩余选项。此外，我们的框架允许用户检查设计解决方案并在各个层次上评估他们的性能指标，帮助他们通过以沉浸式方式搜索/选择/重新聚类解决方案的迭代循环来缩小解决方案空间。最后，我们展示了我们提议的框架的原型，说明了用户如何从 Autodesk 的 Dreamcatcher 软件生成的 16000 多个显示器支架池中导航和缩小所需的解决方案。通过以沉浸式方式搜索/选择/重新聚类解决方案的迭代循环，帮助他们缩小解决方案空间。最后，我们展示了我们提议的框架的原型，说明了用户如何从 Autodesk 的 Dreamcatcher 软件生成的 16000 多个显示器支架池中导航和缩小所需的解决方案。通过以沉浸式方式搜索/选择/重新聚类解决方案的迭代循环，帮助他们缩小解决方案空间。最后，我们展示了我们提议的框架的原型，说明了用户如何从 Autodesk 的 Dreamcatcher 软件生成的 16000 多个显示器支架池中导航和缩小所需的解决方案。