Research On Simulation Of Path Planning For Warehouse Handling Robot

After entering the 21st century,with the development of science and technology and the concept of industry 4.0 and China's intelligent manufacturing 2025,the traditional manufacturing industry is undergoing tremendous changes.AGV,as the most widely used robot in automated warehouse logistics,its development has attracted much attention.The traditional AGV needs to set the motion path manually,and to achieve the purpose of navigation by embedding metal wire or pasting tape.Although these methods can achieve the basic goal,once the motion path is set,it is not easy to change.By using reinforcement learning for path planning,agents can interact with the environment continuously to learn trial and error to obtain path planning data without prior knowledge.The combination of deep learning and reinforcement learning can effectively solve the problems of slow reinforcement learning efficiency and poor data generalization.Aiming at the problem of less research on single AGV multi-objective task scheduling in soft bag workshop,this paper analyzes the scheduling task of AGV car in soft bag material production line of printing enterprises and designs the framework of path planning simulation system of storage and handling robot.After studying the existing task scheduling algorithms,including multi AGV task scheduling and single AGV task scheduling,according to the problem of single AGV multi-objective task,a task scheduling algorithm based on the principle of short distance is proposed to solve the problem of single AGV multi-objective task scheduling in the soft packaging material production workshop.In order to realize the AGV vehicle navigation without prior knowledge,the existing path planning algorithm is studied,and the near end strategy optimization algorithm is realized,which is compared with the traditional path planning algorithm A*.Using the task scheduling algorithm and path planning algorithm,the path planning simulation system of the storage and handling robot is realized,and the relevant implementation details and display interface of the system are shown.The simulation system is used to verify the feasibility of the scheduling algorithm based on the short distance principle and the near end strategy optimization algorithm in the single AGV multi-objective task problem.In the simulation of the system,the scheduling algorithm based on the short distance principle can significantly reduce the total task execution time of AGV,and the near end strategy optimization algorithm also allows the AGV car to search the path without prior knowledge.