| The algorithm prefers rectangular rooms, you'd just need to adjust it a bit. The wall loss function minimizes wall length and tries to regularize angles, so it naturally converges to square-ish rooms: > we compute the norm of the tangent edge vector, which is equivalent to the norm of the 2D normal direction. Minimizing this loss has the following two effects: simplifying the wall between two adjacent rooms by penalizing its length, and aligning the boundary to the coordinate axis by making the coordinates of the tangent vector sparse in 2D. The optimizer also seems like it should handle corridors okay as long as the corridor area is set to something reasonable. A corridor is just a room that is allowed to be long; since the other rooms will try to take up relatively square spaces you should be left with a long connecting area. > And storage spaces have to be sized appropriately to their intended purpose: you don't want three-foot-deep shelves. Like you said, this is the same minimum/maximum width problem that makes corridors wonky. I think this is relatively easily solved, though. A "minimum width" constraint is really just a requirement that no voronoi site is within X distance of a wall. A shelf is a sub-area in a room where there must be 2 borders within X distance of a voronoi point. Things like furniture and kitchen islands are also basically represented like that, as constrained areas. A simpler alternative to complex per-point constraints would be to have area constraints per control point- a bunch of single-point "rooms" inside the actual rooms. In the case of a corridor, since the voronoi cells tend towards a square, you just need to set that area to the minimum width and they should avoid shrinking below that width. |