PLUME: Procedural Layer Underground Modeling Engine

2025-08-28

AI Summary

Existing 3D underground environment models for space exploration suffer from low fidelity, poor scalability, and limited compatibility with AI and robotic validation pipelines. Method: This paper proposes a procedural 3D underground environment generation framework tailored to the diverse geological features of the Solar System. It introduces a flexible, hierarchical modeling architecture that dynamically integrates scientifically informed subsurface structures—including ice layers, lava tubes, and regolith—enabling high-fidelity, customizable scene generation as planetary science knowledge evolves. The framework tightly couples procedural generation with robotic simulation systems, enabling end-to-end integration and validation. Contribution/Results: An open-source implementation supports rapid iteration and testing of diverse subsurface exploration algorithms. Empirical evaluation demonstrates strong applicability and scalability across AI training, autonomous navigation verification, and real-time 3D rendering tasks.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Natural Language Processing: Generation
• Intelligent Robots: Embodied AI

Application Category

• Web Mining and Content Analysis: Web data generation and simulation
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

As space exploration advances, underground environments are becoming increasingly attractive due to their potential to provide shelter, easier access to resources, and enhanced scientific opportunities. Although such environments exist on Earth, they are often not easily accessible and do not accurately represent the diversity of underground environments found throughout the solar system. This paper presents PLUME, a procedural generation framework aimed at easily creating 3D underground environments. Its flexible structure allows for the continuous enhancement of various underground features, aligning with our expanding understanding of the solar system. The environments generated using PLUME can be used for AI training, evaluating robotics algorithms, 3D rendering, and facilitating rapid iteration on developed exploration algorithms. In this paper, it is demonstrated that PLUME has been used along with a robotic simulator. PLUME is open source and has been released on Github. https://github.com/Gabryss/P.L.U.M.E

Problem

• Procedurally generates 3D underground environments for space exploration
• Addresses inaccessible and non-representative terrestrial underground environments
• Enables AI training and robotics algorithm evaluation for subsurface exploration

Innovation

• Procedural generation framework for 3D underground environments
• Flexible structure enabling continuous enhancement of underground features
• Open-source integration with robotic simulation and AI training