Multi-UAVs Task Assignment Based on Fully Adaptive Cross-Entropy Algorithm

Abstract

Multi-UAVs task assignment is regarded as an important problem in the UAV research domain. To assign multi-UAVs tasks efficiently and accurately, a common method of assigning tasks is needed with resource constraints and precedence constraint. Then, we apply fully adaptive cross-entropy (FACE) algorithm to multi-UAVs task assignment, and the resources and the sequence required for three tasks are also taken into account. Through emphasizing the iterative principle of FACE algorithm and utilizing it to handle the multi-UAVs task assignment problem with constraints, the simulations validate that compared with the cross-entropy method and the particle swarm optimization algorithm, the FACE algorithm has fast convergence speed and the strength to solve large-scale allocation problems.