Original scientific paper

https://doi.org/10.31803/tg-20240704100407

Accelerating Game Level Design with Machine Learning: A Unity Module for Procedural Kitchen Generation

Petar Pejić orcid.org/0000-0003-4155-8038 ; Faculty of Information Technology, Belgrade Metropolitan University, Tadeuša Košćuška 63, 11158 Belgrade, Serbia *
Jelena Pejić ; Faculty of Sciences and Mathematics, University of Niš, Višegradska 33, 18106 Niš, Serbia

* Corresponding author.

Abstract

The video game industry faces significant challenges in content creation, with AAA games requiring extensive time and resources. This research addresses these challenges through the development of a Unity module for automatic 3D kitchen model generation using a Machine Learning-based Procedural Kitchen Generation (PKG) model. The module significantly reduces the time needed for game-level design, achieving designs over five times faster than traditional methods. A comparative study shows that the module produces results comparable to industry-standard tools in terms of user preference. This Unity module offers promising potential for commercial use, streamlining the design process and enhancing efficiency in game development.

Keywords

3D Kitchen Models; Game Level Design; Machine Learning; Procedural Content Generation; Unity Module

Hrčak ID:

346371

URI

https://hrcak.srce.hr/346371

Publication date:

15.6.2026.

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