Cluster segmentation algorithm based on the Vicsek with static summoning points

Because of the low convergence efficiency of the typical Vicsek model, a Vicsek with static summoning points (VSSP) algorithm based on the Vicsek model considering static summoning points is proposed. Firstly, the mathematical model of the individual movement total cost on each summoning point is established. Then the individual classification rule is designed according to the initial state of the cluster to obtain the sub-clusters guided by each summoning point. Finally, the summoning factor is introduced to modify the course angle updating formula of the Vicsek model. To verify the effectiveness of the proposed algorithm and study the effect of the cluster summoning factor on the convergence rate, three groups of simulation experiments under different summoning factors are designed in this paper. To verify the superiority of the VSSP algorithm, the performance of the VSSP algorithm is compared with the classic algorithm by designing the algorithm performance comparison verification experiment. The results show that the algorithm proposed in this paper has good convergence and course angle consistency. The summoning factor is the sensitive factor of cluster convergence. This algorithm can provide a reference for efficient cluster segmentation movement.