Research On AGV Path Planning Algorithms And Scheduling Strategies For Intelligent Manufacturing Workshops

The Automated Guided Vehicle(AGV)system is an indispensable part of the intelligent manufacturing workshop.A reasonable and effective AGV system can significantly improve the work efficiency of the workshop.The key technologies that restricts the effectiveness of the system are the AGV path planning methods and system scheduling strategies.This research will be based on the intelligent manufacturing workshop to study the path planning and system scheduling of AGVs.Aiming at the application requirements of the irregular layout of the intelligent manufacturing workshop,a relatively complete AGV path planning solution was proposed.When modeling the working space of the AGV,a topological grid hybrid modeling method is designed,and the advantages of different environmental modeling were used according to local conditions to adopt different modeling methods for different working spaces: using genetic algorithm for path planning in the grid modeling area,and completing the genetic algorithm optimization by improving the fitness function and changing its population selection method.The results of MATLAB simulation experiments show that this optimization effectively improves the smoothness of the path and effectively prevents the traditional method from falling into the local optimum.Shortcomings,simulation analysis of the effectiveness interval of the improved algorithm is also carried out.The results show that the algorithm is effective when the obstacle grid accounts for less than or equal to 40% of the total environment.the breadth-first search algorithm is applied in the topology modeling area and simulated the algorithm process,the effectiveness of the algorithm is verified through a demonstrative model.Aiming at the problem of task scheduling and conflict coordination scheduling in multiple AGV systems,a core solution for AGV scheduling in intelligent manufacturing workshops is designed.This research proposes a priority-based task dispatch strategy and a task integration strategy that can effectively improve system efficiency,and designs an algorithm based on time window arrangement to calculate and deploy the time for each AGV to pass through each channel,so as to avoid common facing and chasing conflicts,a path resource lock is also designed to solve unforeseen conflicts and common node conflicts.Based on the experimental platform OpenTCS,the breadth-first search algorithm,task scheduling and conflict coordination scheduling strategies are expanded and implemented,and the overall design solution is proposed by the system center server to manage the path and time resource allocation,and the effectiveness of the breadth-first search algorithm is simulated and experimentally verified.An algorithm for the batch generation of system tasks is developed,and a complete simulation experiment on the system is conducted.Relying on 5 AGVs to complete 95 tasks within 100 minutes,the completion rate was 100%,which effectively solved the conflict coordination and scheduling problem of multiple AGVs in the system.It verifies the effectiveness and practicability of the scheduling strategies.