 The rational clustering method, RCM, is an algorithm for dense task neighbor information exchange that can be used to cluster objects according to their shared properties. It uses the task density of its neighbors, along with the similarity between them, to identify UAV units completing tasks and free slots. This information exchange process groups together high-slot UAVs within the communication range, preventing tasking completion slash failure and delays in a densely populated UAV scenario. Additionally, it recommends cluster sustainability or dispersion when using distributed state learning. This triple feature-based distributed method balances tasks between failures, overloading, and idle UAVs. The RCM was verified using task processing rate, completion ratio, reassignment, failures, and delay. Task processing rate was increased by 8.16 percent, and completion ratio was increased by 10.3 percent. Reassignment, failure, and delay were all reduced by 12.5 percent, 9.87 percent, and 11.99 percent, respectively. This article was authored by Jian Yang and Xue Junhuang.