Research On Multi-AGV Path Optimization In Intelligent Production Line

As an important means of transportation in intelligent production line scene,automatic guided transport vehicle(AGV)has been widely used in intelligent production line.AGV is the main carrier of material transportation in intelligent production line,widely used in intelligent production line,multi-AGV automatic transport can not be separated from the path planning technology,multi-AGV at the same time work there is a conflict between AGV,multi-AGV path optimization algorithm is challenging,intelligent production line scenario AGV path optimization research is of practical significance.In this paper,the multi-AGV path optimization problem is studied from four aspects,and the main working contents are follows.(1)based on the scene analysis of the typical working environment,the establishment of static and dynamic two kinds of operating environment models.For static working environments,topological method is used to solve the impact of obstacle size and shape on the environment model.For the dynamic working environment,two kinds of environmental models with obstacles are established,namely,the environmental model based on the dynamic obstacle motion direction and the environment model based on the dynamic obstacle motion speed,which overcomes the uncertainty of complex dynamic environment and the influence of environmental detection error on the environmental model.(2)AGV prototype design.In view of the working environment and functional requirements of AGV,the design requirements of AGV are put forward,and according to the design requirements,the design and selection of mechanical structure and control system are completed,the navigation mode of AGV is analyzed,and the problem of precise positioning is solved.(3)Based on the two problems existing in single AGV path planning,the target is una%and the local optimal,a artificial potential field method is proposed,its repulsive potential field function function is studied,and the global path optimization algorithm is improved and obtained.This paper studies the local path planning method,adopts the dynamic window method,controls the evaluation coefficient in the evaluation function,maximizes the dynamic window method,and adapts to the complex environment.Finally,the validity of global and local path planning is verified by using MATLAB simulation experiments.(4)In view of the intersection conflict between AGV in the multi-AGV operating environment,the problem of AGV path(Automatic guided vehicle Problem,ARP)is proposed,and the multi-AGV path optimization problem is solved by cloning selection algorithm.In order to solve the problem of path competition between AGVs,a mathematical model is established.In order to further improve the coordination,the cloning selection algorithm is improved to ensure collision-free driving between AGVs,and the superiority of the algorithm is verified by simulation.This thesis closely combines the characteristics of intelligent production line and the functional requirements of AGV,gives full play to the advantages of intelligent optimization algorithm,and solves the multi-target planning problem of multi-AGV under the typical intelligent production line scene under the premise that AGV does not conflict in the path.