Abstract: The increasing number of space debris has led to frequent collisions among orbiting spacecrafts, posing a huge obstacle to human space exploration. The current distribution of space debris is analyzed with the aim of fewer collision events occurring in areas with dense distribution of space debris. The Density Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm is used to cluster debris based on the fuel consumption required between debris as feature information, and the core objects of debris are determined by the number of neighboring debris that meet the fuel consumption requirements. Satellites that release space vehicles to the vicinity of each debris are selected based on the fuel consumption required, which is equal to the number of clusters. The Hungarian algorithm is used to assign satellite debris cluster clearing tasks, and spacecraft can implement one to many core object clearing tasks in specific clusters.

Key words: debris removal, clustering algorithm, Hungarian algorithm, task allocation