Intelligent Navigation And Scheduling Of Vehicles In Warehouses Based On RFID

Due to the continuous growth of large-scale warehouse centers, storage area and simultaneous assignments increase significantly, which makes it more and more time-consuming for vehicles to seek target shelves and difficult for host to distribute tasks during daily operation. This is the reason why goods turnover efficiency decreases, operating cost soars, and further more, warehouses become the bottleneck stroking the development of logistics industry. According to the situation mentioned above, this paper proposes a novel method which designs an intelligent navigation and scheduling system based on RFID-vehicles, by merging the traditional warehouse information management and vehicle assistant fuctions together.For the purpose of sensing cargo and pallet labels, forklifts are usually equipped with RFID module. It is the very apparatus on which another antenna is added, towards the navigation IC-tags deployed on the ground or ceiling. By matching data between coordinate message sending from these tags and the presetted map information, module can achieve real-time localization and tracking of indoor forklifts as a result.For the requirements of most time-saving and energy-saving, an onboard terminal, bridging RFID module and scheduling center, is deployed to take charge of the navigation fuction. Optimal route is generated by a combinative strategy of topological-index and A* algorithm, fed back to host through wireless network communication, and provided as a convenient steering direction for drivers on software interface.By supplementing the maintenance of vehicles and atlas data to common warehouse information, host PC makes use of an improved genetic algorithm to achieve optimal solution quickly, distribute tasks for each vehicle appropriately and schedule execution order reasonably, which as a result minimizes the global consumption in multi-vehicles or multi-tasks condition. Experiments data illustrate that this design efficiently reduces the implementation cost and turnover time, improves the utilization ratio of storage space as well. So it deserves a promising prospect.