An Intelligent Mixed-reality Simulation and Training Ecosystem for Extreme Environments

Source de subvention

Professeur(e)s impliqués

• Yann-Gaël Guéhéneuc (Concordia) Andréa Lodi; Antoine Legrain; Caroline Aubé; David Meger; David Saussié; Grégory Dudek; Inna Sharf; Gabriela Nicolescu

Résumé

Everyday, thousands of human agents from a wide range of sectors are involved in complex and critical operations requiring strong coordination, interaction with multi-robot systems and other highly innovative technologies: a team of firefighters managing a large fire in hazardous environments, a search & rescue squad aided by rovers and drones looking for avalanche or other disaster survivors, humanitarian operators offering first aid in a post-tsunami scenario, first responders deployed after a terrorist attack.

The success of these critical operations may be seriously jeopardized by the uniqueness of each emergency response situation, the highly dynamic environment, the information overload together with the inexperience of human operators, that may be demanded to take crucial decisions and perform extremely complex processes without having had this unique field experience in real situations. Furthermore, innovative technologies like drones, smart devices or sensors, which may dramatically improve the efficiency of such multi-agent operations, cannot be practically deployed in the field because of both training and testing issues that prevent them from being totally reliable and widely accepted. In fact, state-of-the-art simulation solutions present substantial limitations and constraints, e.g., high deployment costs, unrealistic User Experience (UX), limited or inaccurate simulation libraries and limited scalability, that affect training efficiency, testing robustness and practical applicability.

To fill this gap in large-scale simulation solutions for multi-agent operations fueled by highly innovative technology, e.g., fleets of unmanned aerial vehicles (UAVs), we aim to develop the Intelligent mixed-reality Simulation and training ecosystem for Extreme Environments (I.SEE).

The researcher will work on the security aspects related to I.SEE. We plan to exploit artificial intelligence in order to improve the security level.