A Unified Multi-Objective Optimization Framework for UAV Cooperative Task Assignment and Re-Assignment

Source abstract

This paper focuses on cooperative multi-task assignment and re-assignment problems when multiple unmanned aerial vehicles (UAVs) attack multiple known targets. A unified multi-objective optimization framework for UAV cooperative task assignment and re-assignment is studied in this paper. In order to simultaneously optimize the losses and benefits of the UAVs, we establish a multi-objective optimization model. The amount of tasks that each UAV can perform and the number of attacks on each target are limited according to the ammunition capacity of each UAV and the value of each target. To solve this multi-objective optimization problem, a multi-objective genetic algorithm suitable for UAV cooperative task assignment is constructed based on the NSGA-II algorithm. At the same time, a selection strategy is used to assist decision-makers in choosing one or more solutions from the Pareto-optimal front. Moreover, to deal with emergencies such as UAV damage and to detect of new targets, a task re-assignment algorithm based on the contract network protocol (CNP) is developed. It can be implemented in real-time while only slightly sacrificing the ability to seek the optimal solution. Simulation results demonstrate that the methods developed in this paper are effective.