Using a game engine, we have developed a virtual environment which models important aspects of critical incident scenarios. We focused on modelling phenomena relating to the identification and gathering of key forensic evidence, in order to develop and test a system which can handle chemical, biological, radiological/nuclear or explosive (CBRNe) events autonomously. This allows us to build and validate AI-based technologies, which can be trained and tested in our custom virtual environment before being deployed in real-world scenarios. We have used our virtual scenario to rapidly prototype a system which can use simulated Remote Aerial Vehicles (RAVs) to gather images from the environment for the purpose of mapping. Our environment provides us with an effective medium through which we can develop and test various AI methodologies for critical incident scene assessment, in a safe and controlled manner
@article{arxiv.1808.10784,
title = {Using a Game Engine to Simulate Critical Incidents and Data Collection by Autonomous Drones},
author = {David L. Smyth and Frank G. Glavin and Michael G. Madden},
journal= {arXiv preprint arXiv:1808.10784},
year = {2018}
}