A Virtual Testbed for Critical Incident Investigation with Autonomous Remote Aerial Vehicle Surveying, Artificial Intelligence, and Decision Support

TL;DR

This paper presents a virtual testbed for critical incident investigation using autonomous aerial vehicles, AI, and decision support to enhance safety and efficiency in hazardous scenarios.

Contribution

It introduces a realistic 3D CBRNE scenario testbed for developing and evaluating AI tools for autonomous incident response.

Findings

Developed a detailed 3D CBRNE scenario model

Demonstrated AI tools for scene surveying and risk assessment

Enabled safe testing of autonomous systems in hazardous environments

Abstract

Autonomous robotics and artificial intelligence techniques can be used to support human personnel in the event of critical incidents. These incidents can pose great danger to human life. Some examples of such assistance include: multi-robot surveying of the scene; collection of sensor data and scene imagery, real-time risk assessment and analysis; object identification and anomaly detection; and retrieval of relevant supporting documentation such as standard operating procedures (SOPs). These incidents, although often rare, can involve chemical, biological, radiological/nuclear or explosive (CBRNE) substances and can be of high consequence. Real-world training and deployment of these systems can be costly and sometimes not feasible. For this reason, we have developed a realistic 3D model of a CBRNE scenario to act as a testbed for an initial set of assisting AI tools that we have developed.