Design And Path Planning Of Intelligent Storage Robot

As the demands for logistics automation continues to increase,mobile robots will play an increasingly important role in the warehousing field and become an indispensable part of a modern logistics system.In modern warehousing systems,intelligent storage robots can be used to improve transportation and sorting efficiency,reduce manual intervention,reduce costs and improve safety.Intelligent storage robots can also perform tasks such as autonomous movement,positioning,and path planning in warehousing facilities,thereby improving the efficiency and productivity of the entire logistics system.The design and path planning algorithm of an intelligent storage robots is studied in this thesis.The main work and achievements in this thesis are as follows:(1)Firstly,this paper first analyzes and discusses the theories involved in the design of intelligent storage robots and their path planning.This includes an analysis of the current development status of mobile robots both domestically and internationally,as well as the current research status of warehousing robot path planning algorithms both domestically and internationally.For intelligent storage robots,a comprehensive system plan is designed,including the overall functional design of the intelligent storage robot system,the hardware composition design of the system,and the selection of the tracing control scheme.(2)Next,this paper studies and designs the hardware and software control systems of intelligent storage robots.The research on the hardware system of intelligent storage robots mainly includes the mechanical design of the robot body,the selection of the main control,the design of the motor drive,and the selection of sensor modules.In terms of sensor selection,infrared photoelectric obstacle avoidance sensors,ultrasonic obstacle avoidance sensors,magnetic navigation sensors,etc.were selected as the main sensors.The infrared photoelectric obstacle avoidance sensor and ultrasonic obstacle avoidance sensor collaborate to achieve the automatic obstacle avoidance function of the intelligent storage robot.The research on the software control system of intelligent storage robots mainly includes the analysis of the robot’s motion model,the analysis of the control algorithm,and the design of the overall software process of the intelligent storage robot and the software design of the tracing algorithm.(3)This paper conducts experimental research on intelligent storage robots.Firstly,an experimental platform for intelligent storage robots was built.Secondly,design and test the remote monitoring unit of the intelligent storage robots based on Rospberry Pi.Then,the intelligent storage robots is tested for tracking and positioning,which is divided into linear tracking test and curve tracking test.Finally,an obstacle avoidance test was conducted on the intelligent storage robots to test its safety performance.(4)In conclusion,this paper focuses on studying the path planning algorithm of intelligent storage robots.In order to address the slow convergence speed,low diversity of the initial population,and poor global optimization of the standard slime mold algorithm(SMA),a multi-strategy improved slime mold algorithm(MSMA)is proposed.To verify the performance of the improved algorithm,23 benchmark test functions were selected to compare MSMA with five different algorithms for simulation,and Wilcoxon rank sum detection was performed on the test results.Finally,two different grid map environments with varying complexity were simulated,and MSMA was applied to the global path planning of mobile robots and compared with the standard slime mold algorithm and gray wolf algorithm.The experimental results show that the proposed algorithm has good convergence and global search ability,and compared with the standard slime mold algorithm and gray wolf algorithm,MSMA has better planning efficiency and path finding ability in intelligent storage robot path planning.