Research On Simultaneous Localization And Mapping Algorithm About Automated Guided Vehicles In Automated Storage

With the development of autonomous navigation technology,AGV is widely used in the field of automated storage.The power system test instrument warehouse has a large number of electrical instrumentation equipment that needs to be placed and tested every day.This handling process consumes a lot of labor costs,and often delays the experiment time,and the work is ineffective.Based on this application background,this subject has carried out SLAM technology research for automated storage,completed the construction of the AGV's the odometer motion model and the lidar observation model,tested the laser radar's performance,provided hardware conditions and theoretical basis for subsequent SLAM research.When studying SLAM,positioning and mapping are divided into two independent issues to analysis.Firstly,environmental map construction is studied.Through analysis of three map types,grid map is selected to describe the real application environment.Under the condition of knowing AGV's posture,MATLAB software is used to simulate occupation grid compositing algorithm.After that,the particle filter positioning algorithm is studied.The standard particle filter algorithm has low positioning accuracy and poor stability.The particle filter algorithm positioning accuracy and stability are improved by changing the particle filter's resampling method.The simulation results show that the improved particle filter algorithm positioning accuracy and stability are significantly improved.At the same time,the influence of AGV own system noise attribute on the improved particle filter is also studied in order to better carry out the follow-up SLAM research.Using Qt tools to develop a more user-friendly navigation software platform,on which the AGV can carry goods on a fixed route.The environmental map of the test instrument storage is constructed by the particle filter SLAM algorithm based on system resampling method.The AGV repeatability test is carried out on the map.The experimental results show that the repositioning accuracy of the SLAM algorithm,which meets the project requirements.