AI 3D Mesh Generation...Good Enough To Replace You?

Introduction

Rodan is an AI-powered 3D asset generation tool that aims to help game developers create mesh assets quickly and efficiently. However, the question remains: Is it ready to replace traditional methods, and can it truly meet the quality standards required for game development? This article delves deep into the utility and reliability of Rodan, tested across various mesh categories—basic, complex, and organic. We will also attempt to create a player character suitable for in-game usage.

Testing Basic Mesh: Wooden Crates

For the first test, we tried generating a basic mesh. The input was as follows: "wooden crates," "closed wooden crate," and "wooden crate box with six sides, cube has six sides and cross pieces that create an X on the side." Despite several attempts and adjustments in the prompt, the results were underwhelming.

Initial Impressions: The generated crate was more complex than needed for a simple box. It had unnecessary details and irregularities.
Material Generation: The material appeared AI-generated with issues like messiness and odd designs.
Importing into Blender: When imported, the crate showed shiny, distracting surfaces and some mesh issues.
Conclusion: The basic asset creation was too detailed and had errors that would need manual correction.

Testing Complex Mesh: Laser Pistol

For a more complex asset, we decided to generate something akin to Ratchet's wrench from the game series "Ratchet & Clank."

Image to Mesh: The generated mesh was fairly impressive in terms of shape but lacked the fine details.
Material Generation: The material generated was closer to the original input images but still had some inconsistencies.
Comparison: Against a Sketched model by a professional, the differences were evident in terms of detail and edge sharpness.
Conclusion: While more impressive than the basic mesh, it still lacked detailed edges and fine touches.

Testing Organic Mesh: Tree

The next test involved generating an organic asset: a stylized tree.

Result: Unfortunately, the process kept getting stuck at 90%, making this test inconclusive.
Conclusion: Stuck at 90% thus failing to generate a useable mesh.

Creating a Player Character: Godot Mascot

Finally, we aimed to generate a player character using high-quality images of the Godot mascot.

Image to Mesh: The result was a T-pose model acceptable from afar but rough up close.
Material & Geometry: The material showed several issues often found in AI-generated textures.
Animation & Rigging: While it could be rigged in Mixamo, the quality was still sub-par for game usage.
Conclusion: The character model had an incomplete, unpolished feel and would require significant manual adjustments.

Final Thoughts

After extensive testing over four hours, it's apparent that Rodan has potential but also several critical shortcomings. While it can generate impressive models quickly, they often lack the crisp edges and detail necessary for game development. Moreover, manual clean-up and optimization are still required, meaning that experienced developers may question its time-saving claims.

Rodan is an exciting tool that shows promise, but it is not yet game-ready for professional use.

Keywords

Rodan
AI 3D asset generation
Game development
Mesh quality
Material generation
Image to mesh
Godot mascot
Blender
Mixamo
Topology issues

FAQ

Q1: Can Rodan be used for creating game-ready assets?

A: Not yet. The generated meshes often require additional manual clean-up, especially for game development.

Q2: What are the main issues with Rodan-generated meshes?

A: The primary concerns include too many vertices, lack of hard edges, material inconsistencies, and irregular geometries.

Q3: How does Rodan perform with complex models?

A: While more impressive than basic models, complex models generated by Rodan still lack detailed edges and fine touches compared to professionally made models.

Q4: Is Rodan suitable for creating organic meshes?