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A Virtual Environment with Multi-Robot Navigation, Analytics, and Decision Support for Critical Incident Investigation

David L. Smyth, James Fennell, Sai Abinesh, Nazli B. Karimi, Frank G. Glavin, Ihsan Ullah, Brett Drury, Michael G. Madden

Year
2018
Citations
5
Access
Open access

Abstract

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.

Keywords

Computer scienceIdentification (biology)DocumentationAnalyticsDecision support systemSet (abstract data type)RobotHuman–computer interactionArtificial intelligenceData science

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