Research On Master System And Path Planning Of AGV

With the development of automated logistics systems, flexible manufacture systems and unmanned automated factories, the application of automated guided vehicle(AGV) gradually become more important to improve production efficiency and logistics automatism for enterprises.The development of the AGV systems play an important role in reducing labor cost, improving working conditions, unifying information flow and logistics. As an important part of AGV system,this paper research master system and path planning of AGV based on the development of the visual guidance AGV. The main contents are as follows.Firstly, on the basic of composition and working principle of AGV system, the framework of AGV system was introduced, including on-board control system and ground control system. Then the system flowchart was given.Secondly, AGV path planning was studied. Based on the process of the construction of AGV system working environment and research on single AGV path planning methods, an improved A* algorithm was proposed,which introduces factors of turning, and make AGV path more gentle. Then in order to solve path planning problems of multiple AGV, a dynamic time path model was presented. The model was updated by registering and deleting the registration information of nodes about AGV. Based on the model, a dynamic path planning method based on A* algorithm was presented, which searches effectively the shortest-time path and avoids collision and conflict by testing, classifying and processing potential conflicts.Thirdly, by using object-oriented, modular design, and multithread programming technology, AGV master system software was designed and implemented. The specific implementation of each function module are introduced, including database module, path management module, vehicle management module, task management module,communication module and monitoring management module.Finally, the performance of the software was tested via experiments, which included the test of AGV path planning algorithm. The experiments proved the system can realize theexpected function, and verified the effectiveness and practicality of the AGV path planning algorithms.