This research project investigates how adaptive Augmented Reality (AR) applications can improve the efficiency of drone operations and the experience of operators. Drones, particularly Unmanned Aerial Vehicles (UAVs), are increasingly employed in search and rescue (SAR) missions due to their rapid deployment capabilities and the ability to access hazardous areas or viewpoints that are otherwise unreachable. Operating drones in these high-demanding scenarios requires operators to possess certain cognitive abilities to manage the UAV effectively. Our research aims to develop a situation-aware interaction model that considers data from the task, the UAVs, and the human operator, offering support during demanding missions or low abilities. This model will be integrated into an AR application designed to adjust to the current situation, thereby enhancing operational outcomes and user experience.
BT - Mensch und Computer 2024 CY - Karlsruhe, Germany DA - 09/2024 DO - 10.18420/muc2024-mci-dc-178 N2 -This research project investigates how adaptive Augmented Reality (AR) applications can improve the efficiency of drone operations and the experience of operators. Drones, particularly Unmanned Aerial Vehicles (UAVs), are increasingly employed in search and rescue (SAR) missions due to their rapid deployment capabilities and the ability to access hazardous areas or viewpoints that are otherwise unreachable. Operating drones in these high-demanding scenarios requires operators to possess certain cognitive abilities to manage the UAV effectively. Our research aims to develop a situation-aware interaction model that considers data from the task, the UAVs, and the human operator, offering support during demanding missions or low abilities. This model will be integrated into an AR application designed to adjust to the current situation, thereby enhancing operational outcomes and user experience.
PB - Gesellschaft für Informatik e.V. PP - Karlsruhe, Germany PY - 2024 EP - 2 T2 - Mensch und Computer 2024 TI - Enhancing Drone Operation Efficiency and Operator Experience: Integrating Extended Reality and Adaptive Systems with Situation-Aware Models UR - https://doi.org/10.18420/muc2024-mci-dc-178 ER -