CompanyRemote

Historic Gettysburg 3D STL Model

Deadline: 2026-04-04

Description

Budget: $750 - $1000

I’m building a scale‐model of Gettysburg exactly as it stood in 1863 and need a production-ready STL that I can drop straight onto my 3-D printer. The file must be highly detailed and precise; every street, building footprint, and contour needs to follow the period survey data I’ll supply. You are free to capture or refine the topography with LiDAR, drone photogrammetry, or any combination that gets us there—the method is less important than the accuracy.

What matters is that the finished mesh represents ONLY the 1863 town. Any post-war or modern structures have to be removed or never appear in the first place. The mesh must be watertight, manifold, and already repaired for typical slicers (PrusaSlicer / Cura). Think of it as plug-and-print.

I will hand over high-resolution late-1800s maps, reference photos, and notes on known landmark dimensions. You translate that into a clean digital reconstruction, align it with the present-day terrain where necessary, and output a single (or logically sectioned) STL. Expect iterative feedback; we’ll review renders, verify building placement, fix anything that drifts from the historical record, and then lock the file.

Deliverables • Final watertight STL (ready for FDM or resin) • Low-res preview renders for review • Source point cloud or intermediate file (OBJ/PLY) if generated via LiDAR or photogrammetry

Acceptance criteria • Matches supplied 1863 survey map within visible tolerance • No non-historic structures present • Scales correctly when imported at 1 mm = 1 ft (or agreed scale)

If restoring the past in digital form is your specialty, let’s talk timelines and the best way to exchange data. I want a rapid turnaround for this.

Skills

3D Animation3D Design3D Visualization3D Printing3ds MaxLess3D Modelling3D Print DesignDrone Photography3D Drafting3D Rendering3D CAD

Want AI to find more roles like this?

Upload your CV once. Get matched to relevant assignments automatically.

Try personalized matching