Research on UAV Cluster's Operation Strategy Based on Reinforcement Learning Approach

摘要

It is of necessity to formulate an overall UAV regulation scheme that covers each UAV's path and task implementation in the operation of UAV cluster. However, failure to fully realize consistency with pre-planned scheme in actual task implementation may occur considering changes of task, damage, addition or reduction of UAVs, fuel loss, unknown circumstance and other uncertainties, which thus entail a simultaneous online regulation scheme. By predicting UAV's 4D track, posture, task and demand of resources in regulation and clarifying data set in UAV cluster operation, quick planning of UAV's flight path and operation can be realized, thus reducing probability of scheme adjustment and improving operation efficiency.