A Distributed-Centralized Dynamic Task Allocation Algorithm for UAVs Tracking Moving Targets

This paper studies a task allocation problem in which a team of UAVs collaboratively tracking multiple moving targets with different priorities. In this mission, task allocation is required to decide which UAVs will be assigned to track which targets at each time instant. A dynamic task allocation framework is proposed which integrates a distributed election algorithm and a centralized target assignment algorithm. First, an election algorithm is designed to determine in a distributed manner a leader UAV to make task allocation decisions by which guarantees a new leader will be regenerated immediately when suffering leader failures. A fast online target assignment algorithm is proposed which adopts a relaxation technique to balance efficiency and optimality. The effectiveness of the proposed algorithms is verified by simulation experimental results.