: Starting from a set of hard constraints (e.g., regulatory guidelines) and soft constraints (e.g., quality measures), we formulate a constrained optimization to characterize good building layouts. Then, starting from a discrete set of samples of good layouts, we analytically construct local shape spaces around each discrete layout, and link the local shape spaces via a portal graph. Exploration using the portal graph then reveals a family of layout solutions. Importantly, the user is explosed to only good layouts, simplifying layout exploration. Good building layouts are required to conform to regulatory guidelines, while meeting certain quality measures. While different methods can sample the space of such good layouts, there exists little support for a user to understand and systematically explore the samples. Starting from a discrete set of good layouts, we analytically characterize the local shape space of good layouts around each initial layout, compactly encode these spaces, and link them to support transitions across the different local spaces. We represent such transitions in the form of a portal graph. The user can then use the portal graph, along with the family of local shape spaces, to globally and locally explore the space of good building layouts. We use our framework on a variety of different test scenarios to showcase an intuitive design, navigation, and exploration interface.
Another framework based on building layouts to characterize analytically the local shape space was proposed by REF .
Generating and exploring good building layouts
TOGS
Computer Science