An Ability-Centered Clustering Algorithm for Solving the Construction Problem of Multi-Group Unmanned Platforms

With the rapid development of artificial intelligence technology, unmanned aerial vehicles and unmanned ground vehicles have become increasingly popular as substitutes for humans to perform various search reconnaissance and other tasks. However one unmanned aerial vehicle or one unmanned ground vehicle is difficult to meet the multi-dimensional requirements of the task due to its limited load. This paper conducts research on the construction problem of multi-group unmanned platforms (CPMGUP) based on the requirements of tasks. Firstly, tasks are grouped using the k-means clustering algorithm. Then, an ability-centered clustering algorithm (ACCA) was proposed to solve the CPMGUP based on the requirements of the task groups. Finally, numerical experiments were conducted to verify the effectiveness of the ACCA and compare it with the improved genetic algorithm.