RubbleSim: A Photorealistic Structural Collapse Simulator for Confined Space Mapping
Frost, Constantine, Council, Chad, McGuinness, Margaret, Hanson, Nathaniel
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Oct-24-2025
- Country:
- Asia > Japan
- Kyūshū & Okinawa > Kyūshū > Kumamoto Prefecture > Kumamoto (0.04)
- North America
- Mexico > Mexico City
- Mexico City (0.04)
- United States
- Indiana > St. Joseph County
- Notre Dame (0.04)
- Massachusetts > Middlesex County
- Ohio (0.04)
- Texas (0.04)
- Indiana > St. Joseph County
- Mexico > Mexico City
- Asia > Japan
- Genre:
- Research Report (0.82)
- Technology:
- Information Technology > Artificial Intelligence
- Machine Learning (1.00)
- Robots (1.00)
- Information Technology > Artificial Intelligence