Multiple Task Assignment Algorithms for Unmanned Aerial Vehicles

To fulfill the requirement of assigning task the auction algorithm is widely used. There are many classical auction algorithms those performances not up to the mark while dealing with multi-UAVs dynamic task assignment. SWARM UAVs are made up of a large number of small UAVs with limited mission resources that can operate in an autonomous, appropriate and universal manner. Based on the in-depth research of the traditional auction algorithm CAA, this paper proposes an iterative method that can improve the task allocation efficiency of multi-UAV, namely the two-stage auction algorithm. At the same time, in order to improve the daily management of airborne computing and communication resources of UAV, this paper overcomes the difficulties caused by data coupling between task allocation and path planning, and proposes a decentralized task allocation algorithm, that is, UAV re-checks the unreasonable task allocation results within the task allocation cycle. This method has the advantages of algorithm security and unpredictability, and it can control the error of task assignment evaluation within a specific range through finite complexity calculation. Simulation results show that the algorithm is effective in computing efficiency and task execution efficiency.