Mobile Robot Navigation System Based On ROS And Turtlebot

In recent years,with the development of intelligent technologies,various intelligent mobile robots have gradually entered the basic life of the public.During the COVID-19 outbreak in 2020,the demand for various types of mobile robots has grown rapidly.With the intensification of the aging society,mobile robots will remain a blue ocean in the future.To achieve the intelligence of mobile robots,a good navigation system is indispensable.For this problem,this paper takes Turtlebot mobile robot as the research object,designs and implements a navigation system with automatic navigation,fault recovery,and two-point navigation functions,then tested the functions of the system in the simulation environment.The main research contents of the paper are as follows:First introduced ROS(robot operating system)and some common mobile robots,then analyzed the technical methods used in the common functions of mobile robot navigation,including the basic positioning strategy of mobile robots,mobile robot path planning,global path planning and local path planning.Subsequently,based on the existing research data,the basic requirements of the mobile robot navigation system were analyzed,and the outline design and detailed design of the navigation system were completed based on the ROS framework.Finally,the navigation system was implemented step by step through the module split method.The navigation system in this paper is divided into two major modules: automatic navigation and two-point navigation.When the robot enters an unfamiliar environment,the automatic navigation module can drive the robot to explore and establish an environment map by itself in the unfamiliar environment.This paper made improvements based on existing navigation algorithms and implemented two algorithms to accomplish this function: the obstacle edge detection method based on Brushfire and the free space edge detection method based on potential Map.Two-point navigation is based on the existing environment map,which uses a combination of global path planning and local path planning to move the robot to the specified target point.In the process,local path planning is used to avoid obstacles in real time.Fault recovery is to recover the robot using an appropriate method when the robot accidentally collides or falls,and continue the previous navigation task.Because the actual experimental conditions cannot be met,this paper chooses to conduct various tests of the system in the simulation environment.The experiments in this paper select three types of environments: simple environment,complex environment and willow garage environment.Multiple test results of various environments verify the effectiveness and integrity of the various functional modules of the navigation system designed in this paper.