UAV Swarm Collaborative Transhipment Scheduling with Deep Reinforcement Learning

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