Glock 19 Gen 4 MOS + Weapon Customisation system - University Honours Project

Project Teaser - Featuring 'Million Dollar Baby' by Tommy Richman

Base Glock-19 Gen 4 MOS

The base model was created in Blender, baked in Marmoset, and textured in Substance Painter. This asset was the primary focus of the project which includes full internals optimised for use in a modern game. The model was created to be as accurate as I could through methods such as dimension extrapolation and perspective matching of references from a multitude of sources. Given this asset is intricate both in model and texture and designed to be viewed very close to the player camera, this forced every stage to be held to a standard that I have not held myself to previously

Although I loved every step of the asset creation, the texturing stage was a definite highlight for me, as I got to research the processes used in real-world firearm manufacturing, and the byproducts these methods leave behind such as machining marks from Computer Numerical Control (CNC) machining or the slightly raised edges around roll-stamped text. I then consequentially had to learn how to reproduce these details in Substance Painter which has greatly improved my knowledge of texturing. 

Marmoset Renders:

Render to Wireframe:

Marmoset Viewer:

Process images and Texturing breakdown example:

Customisation system

Project available for download on itch.io HERE

This Gunsmith was created in Unreal Engine 5 to showcase my work in an interactive manor. 

All assets made and textured by me.
(Some high-poly versions of the attachments were remeshed in blender - some were Polished in Zbrush so I could compare the workflows)
All blueprinting done by me.
The majority of U.I. assets created by me (With exception of "Controls" section featuring some altered assets by Kenney - https://kenney.nl/)

U.I. Assets:

Final note:

This project would not have been possible to this standard were it not for the amazing in-depth feedback received from industry members, so a massive thank you to everyone involved with providing feedback and motivation along the way. I must shout out everyone in the Wardog server for their help, and specifically Gabriel Posiunas who has provided the most detailed feedback breakdown I've received to date. This is available to view within the server here: https://discord.gg/8Zvm7Q9Nd2