A CSCM-SA method for Multi-UAV Task Assignment

The unmanned aerial vehicle (UAV) has huge application potential in disaster rescue, natural detection, and military reconnaissance. In these scenarios, task assignment is essential and facing the problem of NP-hard, and as the scale of the Multi-UAV system increase, it is harder to solve the problem. In this paper, a CSCM-SA (Cosine Similarity Clustering Method- Simulated Annealing) is proposed. Firstly, the cosine similarity clustering method is used for pre-clustering of large-scale targets; Secondly, simulated annealing is employed to optimize routers for each UAV; Finally, to cope with the instability of CSCM results, two strategies of employing genetic algorithm are studied. Simulation results show that the CSCM-SA algorithm is effective to conduct task assignments for the large-scale multi-UAV systems.