Research On Optimization Of UAV Stocktaking Operation Based On Internet Of Things And Digital Twin Environment In Warehousing

With the deep cross-border integration development of new generation information technology and advanced manufacturing technology,the market potential of intelligent warehousing and industrial logistics solutions is enormous.The digitalization,networking,and intelligence of warehouse stocktaking operation can not only improve the level of information management but also enhance production service quality,which is of great significance for enhancing the core competitiveness of enterprises.However,the existing warehouse inventory management has pain points such as personalized demand,complex management data,and easy occurrence of discrepancies between accounts and goods.This article proposes a solution for fine-grained management of warehousing,which integrates unmanned aerial vehicle(UAV),industrial internet of things(Io T),and digital twin,to ensure the accuracy of inventory management and the timeliness of inventory sampling tasks.The main research work of this paper is as follows:Firstly,the demand for UAV stocktaking data calculation in Io T warehousing is analyzed.The collection of UAV stocktaking data is completed by deploying various sensors at the warehouse,configuring edge nodes and cloud application services,and analyzing the mechanism of information interaction operation to achieve active perception and interconnection of bottom-level information in the warehouse.By establishing a hidden Markov cloud-edge collaborative computing model for the integrated planning of warehouse logistics and stocktaking,the construction of a warehouse Io T digital twin environment for UAV cloudedge collaborative computing is completed.Secondly,the data collection and information interaction mechanism of stocktaking operation are analyzed.Considering the constraints of danger avoidance and data collection,the energy consumption difference of UAV under flight conditions such as acceleration,deceleration,uniform speed,and turning is considered.A mathematical model for Io T warehousing UAV stocktaking operation is constructed,and the comprehensive applicability function system is quantitatively calculated with the greenness value G as the objective function,considering the factors of minimum energy consumption and shortest time into account.The differential migration-segmented mutation biogeography optimization algorithm is designed to optimize and solve the mathematical model to obtain the optimal stocktaking path.Then,based on the actual departure of UAV stocktaking operation in the warehouse Io T digital twin environment,a digital twin model framework is constructed from the dimensions of "geometry-physics-behavior-rules" to achieve multi-dimensional physical warehousing digital twin modeling,and its virtual-real consistency is verified from the aspects of model and layout.Through digital twin data services such as data processing,storage,and mapping,the Io T warehousing and digital twin warehousing UAV stocktaking operation are synchronously mapped,achieving UAV state visualization and dynamic stocktaking data visualization,and completing the digital twin real-time monitoring of UAV warehousing stocktaking operation.Finally,a corresponding prototype system is developed using C#、Unity3D and Vue architecture,which realizes the dynamic description and real-time display of stocktaking operation,including Io T warehousing data operation,UAV stocktaking path planning,and digital twin warehousing dynamic stocktaking operation.Through prototype system testing and UAV stocktaking operation process analysis,the rationality and effectiveness of the proposed model and methods are verified.