Optimal Task Assignment for UAV Swarm Operations in Hostile Environments

This paper proposes the engagement model and optimal task assignment algorithm for small-UAV swarm operations in hostile maritime environments. To alleviate the complexity of a real engagement environment, several assumptions are made: in the proposed engagement model, a vessel can attack the UAV within a certain range with a constant kill probability rate; and the ability of a vessel to attack UAVs is reduced if the multiple UAVs are involved. The objective function for optimal task assignment is constructed from the engagement model which estimates the total damage to vessels as the engagement outcome. Considering computational time and non-convex nature of the optimization problem, a heuristic approach, SL-PSO (social-learning particle swarm optimization), is adopted to maximize the objective function. In particular, a modified SL-PSO approach is introduced to deal with the optimization problem in a discrete domain. Numerical simulation results for two scenarios are presented to analyze the characteristics of the proposed engagement model and the performance of the optimal task assignment algorithm in the given environment