Unmanned aerial vehicle (UAV) path planning is the key to the UAV carrying a high-precision portable radio frequency identification (RFID) reader to complete an inventory task. By taking a quadrotor UAV as the object, a type of method is proposed for the path planning using a UAV with RFID readers to conduct an inventory of industrial product warehouses. As the particle swarm optimization algorithm (PSO) tends to converge prematurely when solving path planning problems and tends to fall into local optima, PSO has been improved and an improvement method based on differential evolution has been proposed. The fitness-adaptive differential evolution algorithm (FiADE) and PSO are mixed and improved for further application in three-dimensional space. The final simulation results show that the hybrid suitability DE algorithm (PSO-DE) based on improved PSO has a higher uniformity than the DE algorithm, PSO, and whale optimization algorithm (WOA), and is more suitable for the trajectory planning of drones in complex industrial warehouses.