Scan-to-Simulation Workflow: Wooden Box Asset for Unreal Engine

A physical wooden box was scanned, cleaned, optimized, scale-validated, and imported into Unreal Engine for basic visualization and simulation-readiness testing. The final asset was reduced to approximately 42k triangles and tested for scale, placement, collision, material display, and performance.

1. Object Scanning

The wooden box was captured using Scaniverse on iPhone. Multiple angles were scanned to capture the top, sides, corners, and lower edges of the object.

Goal: collect usable real-world 3D data for a scan-derived Unreal asset.

2. Mesh Cleanup and Optimization

The raw scan was imported into Blender for cleanup and optimization. Unwanted scan fragments were removed, the mesh was reoriented, scale was checked, and the polygon count was reduced while preserving the main shape.

Goal: prepare a clean and lightweight scan mesh for Unreal Engine.

Key result:
The optimized model was reduced to approximately 42k triangles.

Technical note:
Full quad retopology was not required. The asset remains a cleaned triangular scan mesh, suitable for visualization, placement, and basic collision testing.

3. Scale Validation

The physical box was measured and compared with the digital model to verify real-world scale.

Goal: confirm that the Unreal asset matches the physical object within an acceptable visualization tolerance.

Target:
Main dimensions should be within approximately 1–3% for basic visualization and placement testing.

Measurement dimension differences compare with physical object:

4. Unreal Engine Validation Tests

A simple Unreal test scene was created to validate the asset for basic simulation-readiness.

Goal: test whether the asset works correctly in a real-time environment.

Test results:

6. Outcome

The final result is a scan-derived wooden box asset prepared for Unreal Engine. The project demonstrates a compact workflow for 3D data capture, mesh cleanup, optimization, scale validation, Unreal import, and basic technical testing.

Final result:
A cleaned, optimized, and validated Unreal Static Mesh suitable for basic visualization and placement testing.

7. Limitations and Next Steps

This project focused on a compact technical workflow rather than creating a fully game-ready hero asset. The mesh was not fully retopologized, and collision was simplified for basic placement and blocking tests.

Future improvements:

• Cleaner UV/material setup
• Custom collision refinement
• LOD or Nanite comparison
• Manual retopology for production use
• More precise scan measurement validation