Despite well-reported instances of robots being used in disaster response, there is scant published data on the internal composition of the void spaces within structural collapse incidents. Data collected during these incidents is mired in legal constraints, as ownership is often tied to the responding agencies, with little hope of public release for research. While engineered rubble piles are used for training, these sites are also reluctant to release information about their proprietary training grounds. To overcome this access challenge, we present RubbleSim -- an open-source, reconfigurable simulator for photorealistic void space exploration. The design of the simulation assets is directly informed by visits to numerous training rubble sites at differing levels of complexity. The simulator is implemented in Unity with multi-operating system support. The simulation uses a physics-based approach to build stochastic rubble piles, allowing for rapid iteration between simulation worlds while retaining absolute knowledge of the ground truth. Using RubbleSim, we apply a state-of-the-art structure-from-motion algorithm to illustrate how perception performance degrades under challenging visual conditions inside the emulated void spaces. Pre-built binaries and source code to implement are available online: https://github.com/mit-ll/rubble_pile_simulator.

翻译：尽管已有大量关于机器人在灾难响应中应用的报道，但关于结构坍塌事故内部空隙空间组成的数据却鲜有公开。这些事件中收集的数据常受法律限制，其所有权通常归属于响应机构，几乎不可能为研究目的而公开。虽然工程化瓦砾堆被用于训练，但这些场地同样不愿公开其专有训练场地的信息。为克服这一数据获取难题，我们提出了RubbleSim——一个用于光真实感空隙空间探索的开源、可重构模拟器。模拟资产的设计直接基于对不同复杂度训练瓦砾场地的多次实地考察。该模拟器在Unity中实现，支持多操作系统。模拟采用基于物理的方法构建随机瓦砾堆，可在保留绝对地面真实值的同时，快速迭代生成不同的模拟世界。利用RubbleSim，我们应用最先进的结构从运动算法，阐明了在模拟空隙空间内具有挑战性的视觉条件下感知性能如何退化。预构建的二进制文件及实现源代码已在线发布：https://github.com/mit-ll/rubble_pile_simulator。