Fire as a Service: Augmenting Robot Simulators with Thermally and Visually Accurate Fire Dynamics

TL;DR

This paper introduces Fire as a Service (FaaS), a framework that enhances robot simulators with accurate fire dynamics, enabling better training, hazard assessment, and safe deployment of robots in fire environments.

Contribution

FaaS is a novel, scalable co-simulation framework that integrates high-fidelity fire dynamics into existing robot simulators without disrupting control loops.

Findings

Successfully integrated with diverse simulators

Generated realistic thermal and visual fire data

Enabled training of reactive policies via behavioral cloning

Abstract

Most existing robot simulators prioritize rigid-body dynamics and photorealistic rendering, but largely neglect the thermally and optically complex phenomena that characterize real-world fire environments. For robots envisioned as future firefighters, this limitation hinders both reliable capability evaluation and the generation of representative training data prior to deployment in hazardous scenarios. To address these challenges, we introduce Fire as a Service (FaaS), a novel, asynchronous co-simulation framework that augments existing robot simulators with high-fidelity and computationally efficient fire simulations. Our pipeline enables robots to experience accurate, multi-species thermodynamic heat transfer and visually consistent volumetric smoke without disrupting high-frequency rigid-body control loops. We demonstrate that our framework can be integrated with diverse robot simulators to generate physically accurate fire behavior, benchmark thermal hazards encountered by robotic platforms, and collect realistic multimodal perceptual data. Crucially, its real-time performance supports human-in-the-loop teleoperation, enabling the successful training of reactive, multimodal policies via Behavioral Cloning. By adding fire dynamics to robot simulations, FaaS provides a scalable pathway toward safer, more reliable deployment of robots in fire scenarios.