Award

The asymmetric warfare common today requires engagement of small groups and even solitary combatants. Currently, each unmanned system used for surveillance requires a single operator, and, collaboration between operators must be moderated in a complicated fashion. This configuration is not an effective usage of manpower and hinders the efficiency necessary for time-critical geolocation of elusive targets. However, state of the art methods of multi-robot teaming have the potential to allow a single operator to control multiple unmanned systems, interacting with them at a high level. Such an approach will enable the unmanned systems to operate autonomously for extended periods, working collaboratively to pinpoint targets of interest. Our approach ties together three important multi-robot teaming components into a Collaborative Engagement system that can operate in the current architecture used by ARDEC. First, we will use a Mission Planner, developed under current ARDEC funding for the Overseer program to set up and manage mission threads. Second, we will use a formulation called Decentralized Data Fusion that enables an efficient and robust means of integrating data from multiple sources. Third, we will use a state of the art coordination scheme that allows each unmanned vehicle to operate in a distributed manner as it plays its role as a part of the team.