关键词: 无人机, 盘库作业, 射频识别, 三维环境航迹规划, 差分进化算法, 生命周期群搜索算法

Abstract: Stocktaking work is an important link in the invoicing system of industrial enterprises.Aiming at the current shortcomings of manual stocktaking work such as low efficiency and error-proneness,the technology of allowing drones to be equipped with high-precision portable radio frequency identification readers for stocktaking is emerged in recent years,and the trajectory planning is a key issue that needs to be resolved among them.To reduce energy consumption and improve inventory efficiency,the lowest energy efficiency ratio and time efficiency ratio were taken as the goal to construct the objective function,and the corresponding mathematical model of UAV route planning was established.In this model,a hybrid Differential Evolution (DE) Algorithm based on Life-cycle Swarm Optimization (LSO) algorithm was proposed.The actual environmental data of a raw and the auxiliary material warehouse of a tobacco industry company were used for physical modeling,and the simulation experiment was carried out by using the proposed intelligent optimization algorithm.In the same environment,compared with the other three cutting-edge trajectory planning algorithm,the experimental results showed that the route planned by the proposed algorithm could effectively improve the efficiency of UAV stocktaking.

Key words: unmanned aerial vehicle, stocktaking work, radio frequency identification, track planning in 3D environment, differential evolution algorithm, life-cycle swarm optimization algorithm