Application of Improved K-means Clustering Algorithm in UAV Reconnaissance Mission Planning
Xiao Wang, Hanyang Chen, Tao Liu, Kaifeng He, Di Ding, Enmi Yong · 2021 China Automation Congress (CAC) · 2021
In this paper, an improved K-means clustering analysis algorithm is proposed, which is applied to the situation that there are too many reconnaissance targets in the battlefield environment. The purpose is to reduce the number of target points, so as to reduce the number of reconnaissance tasks of UAV, so that the UAV can achieve the same reconnaissance effect at a shorter distance. After the clustering analysis of target points, the traditional genetic algorithm is used to plan the trajectory for the UAV. According to the results, the reconnaissance effect before and after the improvement is compared. The results show that the improved method reduces the number of reconnaissance points and the length of the UAV’s trajectory, and achieves better optimization effect with less cost.