Study on software self-adaptive mechanism for intelligent AGV scheduling system

Zheng Tingting; Wang Dong; Liu Weijing; Xu Wenli; Dang Xing; Wang Junde

doi:10.16186/j.cnki.1673-9787.2024070019

Abstract：Objectives Traditional AGV scheduling systems were found to struggle with adapting to dynamic changes in user needs and environments in practical applications,exhibiting issues such as slow demand response and rigid scheduling strategies.Methods Integrating a multi-level design structure of"user+soft-ware+hardware",a software adaptive mechanism for intelligent AGV scheduling systems was proposed,.Based on the adaptive theory of"data perception,design decision-making,and execution feedback",mul-tiple aspects,including task scheduling,path planning,traffic control,battery management,and commu-nication management,were comprehensively considered within the software adaptive system.The system's response speed and scheduling efficiency were improved from a global perspective to enable real-time per-ception and dynamic adjustment to changes in AGV task demands and environments.Firstly,rapid import technology was used to capture user needs,which were then converted into recognizable raw data for the system based on rule mapping.Secondly,by matching with a preset scheduling strategy pool,relevant pa-rameters of key influencing factors were identified to select the most suitable working mode for executing AGV tasks in the current scenario.Additionally,the adaptive mechanism continuously optimized the sched-uling strategy pool based on real-time feedback from execution results,adapting to new demands and envi-ronmental changes.Results The experimental results indicated that the speed of collecting and applying user needs was significantly improved.The response time was no longer than 300 ms.After using the adap-tive mechanism design framework,the overall operational efficiency of AGVs was increased by 36%.Con-clusions The software adaptive mechanism significantly enhanced the response speed,scheduling effi-ciency,and data accuracy of AGVs.It effectively adapted to complex work demands in specific working scenarios.The system flexibility and adaptability were improved.