Algorithms for Ground Soldier Based Simulations and Decision Support Applications

The Army has invested millions of dollars in large computer generated forces (CGF) applications, supporting constructive and virtual use cases. These applications have embedded algorithms and concepts intended to help simulated entities make automated decisions. These algorithms could directly benefit soldiers outside of a training context, including support for mission rehearsal, tactical decision aids, what if analysis, and more. Similarly, algorithms developed for the operational community, such as Battlefield Terrain Reasoning Awareness (BTRA) could benefit the CGF systems. Opportunities exist to create common algorithms for tactical decision aids supporting both the constructive and operational communities. For Phase I, we propose to focus on two key"foundational"aspects. First, we will focus on low-level terrain and situational awareness primitives required to automate behaviors, such as cover and concealment locations and path planning. Second, we will focus on practical, real world mechanisms to push such low-level decision aids to front line soldiers on mobile or embedded platforms. For Phase II and beyond, Dignitas will focus more on automated behavior generation and automation, both to support CGF scenario planning and advanced tactical decision aids for an operational context.