用程序化生成技术构建可扩展的3D地下环境，助力太空探索模拟。
PLUME: Procedural Layer Underground Modeling Engine
- 基于程序化算法动态生成多样地下结构，支持持续迭代升级。
- 已集成机器人仿真系统，可用于算法训练与测试。
- 开源可用，适合航天模拟、机器人开发等研究者使用。
随着空间探索的发展，地下环境因其提供庇护、资源获取便利及科学价值日益受到关注。尽管地球上存在地下环境，但通常难以进入，且无法准确反映太阳系中地下结构的多样性。本文提出PLUME——一个用于快速生成3D地下环境的程序化建模框架。其灵活架构支持对多种地下特征进行持续增强，契合我们对太阳系认知的不断深化。使用PLUME生成的环境可用于人工智能训练、机器人算法评估、3D渲染以及探索算法的快速迭代。本文展示了PLUME与机器人仿真器的结合应用。该框架已开源，发布于GitHub：https://github.com/Gabryss/P.L.U.M.E。
原文摘要 · Abstract (English)
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
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