The efficiency of multi-Unmanned Aerial Vehicles (UAVs) cooperative operations relies on precise path planning and reliable conflict resolution mechanisms. To address the poor adaptability of existing algorithms in complex dynamic environments, low conflict resolution efficiency in large-scale systems, and the neglect of communication constraints, this paper proposes a multi-UAV cooperative path planning algorithm (DPCM-CCA*) that integrates a Dynamic Priority Coordination Mechanism (DPCM) and a Cooperative A* algorithm with communication constraints (CCA*). The algorithm dynamically adjusts UAV planning priorities through environmental threat assessment, and subsequently introduces multi-dimensional cost evaluations—including path length, turning angle, obstacle avoidance, collision prevention, and communication maintenance—into the heuristic function of path search. This establishes a unified framework for both global cooperative path planning and local replanning under sudden obstacles. Simulation results demonstrate that, compared with mainstream algorithms, the DPCM-CCA* algorithm can effectively shorten the total flight distance and improve conflict resolution efficiency while ensuring continuous communication links and zero collisions, providing reliable technical support for the practical application of multi-UAV cooperative operations in complex dynamic environments.