SELF organized UAV swarm planning optimization for search and destroy using swarmfare simulation

As military interest continues to grow for Unmanned Aerial Vehicle (UAV) capabilities, the Air Force is exploring UAV autonomous control, mission planning and optimization techniques. The SWARMFARE simulation system allows for Evolutionary Algorithm computations of swarm based UAV Self Organization (SO). Through Swarmfare, the capability exists to evaluate guiding behaviors that allow autonomous control via independent agent interaction with its environment. Current results show that through an implementation of ten basic rules the swarm forms and moves about a space with reasonable success. The next step is to focus on optimization of the formation, traversal of the search space and attack. In this paper we cover the capabilities, initial research results, and way ahead for this simulation. Overall the SWARMFARE tool has established a sandbox in which it is possible to optimize these and build new behaviors.

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