Mission Oriented Flocking and Distributed Formation Control of UAVs

This paper presents the development of a novel autonomous search, detect and task execution model for Unmanned Aerial Vehicle (UAV) distributed formations. This work studies the problems of formation flocking, tracking and collision avoidance for a distributed formation of UAVs by use of multi-agent graph theory and artificial potential field approach in the first stage, based upon the proposed algorithm the second stage implements target search, detection and mission execution tasks, while the last stage carries out the reflocking of the vacant UAVs. In order to validate the model, simulations were performed for every stage of the process to evaluate the desired flocking and task execution performance of the distributed formation. Finally, the results obtained from the simulations indicate that UAVs using the proposed model are able to execute the mission as per desired performance goals.