As intelligent manufacturing continues to emerge as a dominant industrial paradigm, unmanned aerial vehicles (UAVs) have proven instrumental in enhancing workshop transhipment efficiency through their inherent operational flexibility. In this paper, we develop a comprehensive UAV swarm collaborative transhipment scheduling model with respect to three-dimensional continuous environments, and introduce Soft-QMIX that systematically integrates maximum entropy with an order-preserving transformation mechanism into collaborative transhipment scheduling tasks, which shows that it can effectively enhance the strategy exploration capability within three-dimensional continuous action spaces and significantly improve UAV’s ability to achieve globally optimal strategies. Besides, a comprehensive simulation environment for three-dimensional UAV swarm scheduling is constructed, with experimental evaluations conducted under different UAV swarm sizes. The results reveal that Soft-QMIX consistently delivers superior cumulative rewards, loss stability, and execution efficiency, approximately achieving 7% increase in cumulative reward for 4-UAV swarm and 5% increase for 8-UAV swarm compared with QMIX. Meanwhile, compared with QMIX, the execution efficiency is improved approximately by 8% and 12.5% for 4-UAV and 8-UAV swarm, respectively. Our work will provide insights for collaborative transhipment scheduling of UAV swarm in complex three-dimensional continuous scenes.
Wang et al. (Wed,) studied this question.