Accidents and attacks that involve chemical, biological, radiological/nuclear or explosive (CBRNE) substances are rare, but can be of high consequence. Since the investigation of such events is not anybody's routine work, a range of AI techniques can reduce investigators' cognitive load and support decision-making, including: planning the assessment of the scene; ongoing evaluation and updating of risks; control of autonomous vehicles for collecting images and sensor data; reviewing images/videos for items of interest; identification of anomalies; and retrieval of relevant documentation. Because of the rare and high-risk nature of these events, realistic simulations can support the development and evaluation of AI-based tools. We have developed realistic models of CBRNE scenarios and implemented an initial set of tools.
@article{arxiv.1806.04497,
title = {A Virtual Environment with Multi-Robot Navigation, Analytics, and Decision Support for Critical Incident Investigation},
author = {David L. Smyth and James Fennell and Sai Abinesh and Nazli B. Karimi and Frank G. Glavin and Ihsan Ullah and Brett Drury and Michael G. Madden},
journal= {arXiv preprint arXiv:1806.04497},
year = {2018}
}
Comments
27th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden