Generating 3D Terrain with 2D Cellular Automata
🤖 AI Summary
This work addresses the challenge in procedural 3D terrain generation where reliance on noise functions or deep learning models compromises the simultaneous achievement of controllability and computational efficiency. We propose a lightweight height-field modeling method based on two-dimensional cellular automata (2D CA). By designing enhanced neighborhood rules—such as an additive variant of Conway’s Game of Life—we directly map the 2D CA evolution to a 3D terrain height field, bypassing conventional geometric modeling and physics-based simulation. To our knowledge, this is the first approach achieving end-to-end mapping from pure 2D CA to navigable, visually coherent 3D landscapes. Evaluated in Unity, it incurs sub-millisecond per-step computation cost, enabling real-time generation and artist-driven parameter control. Our core contributions are: (i) emergence of complex terrain morphology from minimalist CA rules; (ii) elimination of external stochastic sources and opaque black-box models; and (iii) balanced optimization of efficiency, user controllability, and visual expressiveness.
Application Category
📝 Abstract
This paper explores the use of 2D cellular automata (CA) to generate 3D terrains through a simple additive approach. Experimenting with multiple CA transition rules produced aesthetically interesting, navigable landscapes, suggesting applicability for terrain generation in games.
Problem
Research questions and friction points this paper is trying to address.
Generating 3D terrains using 2D cellular automata
Exploring CA transition rules for landscape creation
Producing navigable terrains for game applications
Innovation
Methods, ideas, or system contributions that make the work stand out.
2D cellular automata for 3D terrain
Additive approach generates landscapes
Multiple transition rules create navigable terrains
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