Research On Task-driven Multi-AGV Scheduling Strategy And Path Plannin

As an important tool in modern intelligent logistics,Automated Guided Vehicle(AGV)has effectively promoted the transformation and development of traditional enterprises towards intelligence and automation.At present,the railway transportation of chemical fertilizer enterprises still adopts manual handling and forklift handling,which has the problems of high labor cost,low transportation efficiency,poor safety,low automation and intelligence.Therefore,this paper introduces AGV into the transportation link of fertilizer railway transportation to upgrade the traditional operation mode,preliminarily explores the new intelligent transportation operation mode under the railway transportation environment,and promotes the transformation of fertilizer enterprises to automation and intelligence,so as to improve the market competitiveness of enterprises.This paper mainly studies the task scheduling and path planning of multi-AGV.The specific work is as follows :(1)Based on the platform carrying operation environment of a chemical fertilizer enterprise in Guizhou,the layout scheme of fertilizer stacking is designed according to the constraints such as the length and width of the platform space,the position of the structural column and the size of the fertilizer tray.After clarifying the layout scheme of fertilizer stacking in the platform stacking area,the existing environmental modeling related technologies are analyzed in detail and the grid modeling method is used to establish the environmental factor model,which lays the foundation for the subsequent research.(2)Based on the analysis of the characteristics of fertilizer platform carrying operations and the needs of enterprises,the main scheduling optimization goal is to balance the workload of carrying tasks and the corresponding mathematical model is constructed.An Improved Particle Swarm Optimization(IPSO)algorithm is proposed to solve the task scheduling problem.On this basis,a task matching selection method based on K neighbor space is proposed to further improve the quality of task allocation.The experimental results of different examples show that the comprehensive performance of IPSO is obviously better than the other five mainstream algorithms,and it can solve higher quality task allocation schemes.(3)Aiming at the problems of conflict and collision in multi-AGV path planning in platform reactor area,a decoupled path planning algorithm is proposed.Firstly,the energy consumption factors in AGV motion process are considered,and the energy consumption model is established.The ESA* algorithm with energy consumption cost as the new criterion is proposed,and the path is optimized by combining dynamic benchmark turning penalty,triangular pruning and chorded arc transition method to solve the path planning problem of single AGV.Then,in order to improve the path re-planning ability of local conflict areas,a two-stage motion planning method combining ESA* and IDWA algorithms is proposed.Then,the conflict collision types between AGVs are analyzed,and the conflict dynamic priority strategy is proposed.Combined with the collision conflict autonomous coordination strategy to solve the collision problem of multiple AGVs in the local path.The experimental results show that the proposed method can effectively solve the collision problem between multiple AGVs.(4)Based on the above research,an AGV task scheduling and path planning prototype system is developed,which realizes the task allocation and path planning of multi-AGV in the platform stacking area,and provides a new idea for the railway fertilizer delivery operation mode.