Optimized Planning and Tasking for the Intelligent Management of Unmanned Aerial Vehicles (OPTIM-UAV)

Warfighters in small expeditionary units are faced with rapidly re-allocating and re-tasking multiple unmanned air vehicles to support time-critical intelligence needs, despite limitations in communications and resources. To meet these challenges, warfighters need model-based tools to optimize task allocation based expressly on operator intent and mission objectives, and these tools must be directly coupled with intuitive displays to support situation awareness. Building on the work of the MiDAS (Mission Displays for Autonomous Systems) project, we propose Optimized Planning and Tasking for the Intelligent Management of Unmanned Aerial Vehicles (OPTIM-UAV), an innovative method for optimizing asset allocation of UAVs through the definition of flexible control algorithms, which are shaped and informed by an abstraction hierarchy, or a framework of mission objectives and constraints. Collectively, these structures drive the design of a task allocation interface, ensuring the tight coupling between the optimization algorithms and the operator's understanding of the algorithmic output and mission space. In Phase I, we will collaborate with the University of Iowa to build a framework to model mission objectives and constraints; construct a set of flexible control algorithms to optimize task allocation; develop an innovative plan to link these structures; and demonstrate the functioning model and interface storyboards.