Research On Control System Of Crawler Intelligent Security Patrol Robot In Park

In recent years,with the maturity of robotics and the development of society,intelligent robots were appeared and gradually applied to various aspects of production and life.In park inspection,traditional manual inspection and fixed equipment inspection have different degrees of defects,and the use of inspection robots with autonomous navigation ability has become a hot spot for research,but in practical application with the difference in system design and algorithms show different problems.And with the progress of technology and the needs of society,the requirements for inspection robots are getting higher and higher.In the face of the shortcomings of the current intelligent security inspection robot,this thesis studies and analyzes the control system and improves the path planning and trajectory tracking algorithm to design a crawler-type intelligent security inspection robot with autonomous navigation and inspection capabilities,the specific work is as follows:Firstly,the current status of research on intelligent inspection robots is summarized and described,with emphasis on the algorithms currently used and the shortcomings.Analyze the working environment and working demand of the security inspection robot,and choose the crawler chassis as the moving mechanism of the inspection robot for the uncertainty of the road condition in the park,and use the DC brush motor to realize the closed-loop control.For the demand of autonomous navigation,Raspberry Pi and virtual machine equipped with ROS are used as the development environment,and the map building and navigation functions are realized by carrying LIDAR,and STM32 microcontroller is used to control the motor movement and data reading.Secondly,to address the defects of traditional A* algorithm security and artificial potential field algorithm,the path generation value evaluation function is improved on the basis of A* algorithm,and the security factor is added to improve the planning path security.On the basis of artificial potential field method,distance factor function and velocity repulsion function are added for the problem of target unreachability and high-speed obstacles.Finally,the key nodes of the safety A* algorithm are extracted,the safety A* algorithm and the improved artificial potential field method are fused,and the practicality and reliability of the fusion algorithm are proved by simulation experiments.Then,a motion controller based on fuzzy control and Lyapunov function is proposed for the problem of low efficiency of traditional track tracking control algorithm.The kinematic model and error matrix of the tracked robot are analyzed,and the controller is designed to control the linear and angular velocities of the robot by the Lyapunov function,followed by the design of a fuzzy controller to adaptively adjust the motion controller parameters.And the model is built by MATLAB/Simulink for simulation experiments,and it is concluded that the error tends to zero in finite time,which proves the effectiveness of this control method.Finally,the ROS development environment is established and the prototype is built,and the robot map building is completed using the Gmapping algorithm.The navigation experiments are conducted under the existing map,using the safe A* algorithm for planning after path smoothing,and the fusion algorithm for local planning of temporary obstacles.And the experiments are conducted in a real physical environment,where the robot can reach the set target point from the starting point,and the RVIZ visualization tool in ROS is used on the virtual machine to view and verify the feasibility of the algorithm.