Research On Task Allocation And Path Planning Of Multi-AGV In Warehouse Environment

With the development of e-commerce,intelligent warehousing system has been widely used.Compared with the traditional warehousing system,the intelligent warehousing system has the advantages of low operation cost,strong flexibility and high flexibility.In the intelligent warehouse system,the core link is the task allocation and path planning of multi-AGV(Automated Guided Vehicle).At present,the problem of multi-AGV task allocation is mainly studied with the minimum total moving distance of multi-AGV as the optimization objective.However,in the actual work,AGV will also face the problems of unbalanced load and long task completion time,which makes the operation efficiency of multi-AGV system poor.At the same time,in the global path planning of AGV,AGV will turn too many times and fall into the local optimal path.With the increase of the number of AGVs in the system,the probability of collision increases.Based on this,this thesis makes a further study on the task allocation and path planning of multi-AGV,and the main research contents are as follows:(1)According to the working characteristics of AGV in intelligent warehouse environment,the concept of task chain is proposed.On this basis,a multi-objective multi-AGV task allocation model is constructed with the total moving distance,load balancing degree and task completion time as the optimization objectives.Combined with the genetic algorithm designed in this thesis,the problem of task allocation among multi-AGV is solved.(2)The global path finding method of AGV is optimized to ensure that the system can plan a better initial path for each AGV.Without considering the collision problem between AGVs,the ant colony algorithm is selected to solve the problem with the shortest AGV total path as the optimization objective.The key parameters of the algorithm are dynamically adjusted to enhance the convergence speed of the algorithm.According to the characteristics of grid environment map,the heuristic function of the algorithm is modified,the path guidance function is added,and the concept of grid superiority is put forward,which reduces the probability of the algorithm falling into local optimum when searching the path.(3)Aiming at the collision problem between multiple AGVs,an offline online two-stage cooperative collision avoidance method is proposed.Firstly,the initial path of each AGV is detected to find out the potential conflicts in the path and resolve them offline.On this basis,considering the path conflict of AGV in the process of moving due to error accumulation and fault,the possible conflict types of AGV in the process of moving are analyzed,and the corresponding resolution strategy is designed,combining with the priority of AGV to carry out online conflict coordination.(4)The method and strategy proposed in this thesis are verified by experiments.Firstly,the environment model of intelligent warehouse is built by MATLAB software.On this basis,the task allocation and path planning of multi-AGV are simulated.The experimental results show that the method designed in this thesis can effectively improve the utilization rate of AGV for map environment,reduce unnecessary path loss,and improve the work efficiency of intelligent warehousing,which provides a new idea for the research of such problems.Finally,the AGV car is used to carry out the path planning experiment,and the reliability of the method is further verified.