Distributed battle management of autonomous agents requires controlling a group of semi-isolated small teams, operating under extensive uncertainty about the enemy situation and also about the status and plans of some of our own assets. To minimize waste of resources, isolated agents make predictions about what other agents are planning to do. If these predictions are good, the vehicles will be able to coordinate effectively even during communication blackout periods. However, in cases were the communication black-outs are long as compared to the natural time constants of the mission, the knowledge on the state of the remote agent may become stale. As a consequence, the number of predicted possible paths for the remote agent will grow, increasing the computation load and uncertainty for the local agents lowering the teams ability to coordinate. Barnstorm Research has developed RTREVE, a set of algorithms to support autonomous collaboration in communication challenged environments. RTREVE equipped teams are able to perform collaborative behaviors robustly, even when facing attrition and a challenging communications environment. For SBIR N193-141 we propose to implement RTREVEs autonomous behaviors and supporting algorithms as RAIDER/FACE compliant Units of Portability (UoPs) and to verify their performance in simulation.
Benefit: The natural transition path for RTREVE is to be incorporated into autonomous teams of UAVs developed with mission management software developed under the RAiDER umbrella. The open standards of RAIDER will facilitate incorporating RTREVE technology, developed through multiple DoD funded research efforts, into systems that will support the DoD mission. The recent emergence and rapid growth of the sharing economy provides excellent commercial opportunities for RTREVE technology, when multiple independent providers have to coordinate to deliver a complete service
Keywords: Autonomous Behaviors, Autonomous Behaviors, Robust Coordination, Denied Environments
