The Royal Institution for the Advancement of Learning/McGill University

Published purpose

This project proposes the development of AI-based tools for the identification and monitoring of environment dynamics, their effect on a remote robotic platform behavior, and the adaptation of the latter to maintain stability and performance. The AI tools that will be developed during this project will contribute to increasing the level of autonomy of aerial cargo systems by providing adaptability to unknown and changing environment conditions (related to both remote site and human operator). By monitoring system behavior, these AI tools will also contribute to optimizing the dynamic response of these cargo systems during operation, thereby maximizing safety and reliability. The implementation and validation of these tools using digital twins and virtual environments will also bring the capacity for planning new operations, training and system robustness evaluation in the presence of unknown and changing conditions.