Research On Simultaneous Localization And Mapping Of Mobile Robot With Laser Range Finder

In this paper,the simultaneous localization and mapping study of the mobile robot based on laser range finder.After twenty-first Century,the robot has a more prominent effect on human beings.Robot is a typical product of the intelligent era,and the mobile robot is the most representative and most common of the intelligent robots.With the development of technology,the requirement of mobile robot is increasing,and the ultimate goal is to make mobile robot to achieve real autonomy and intelligence.When the mobile robot carries out a task,the map is generally known.When the map is unknown,the robot needs to know the map information when move around,so the robot needs to draw a map first.When the robots draw a map,they must know their position.So the map information and location information of mobile robot are mutually important.Simultaneous Localization and Mapping,is a robot a particular sensor,in the process of moving to detect unknown environment and obtain some information around,in order to realize their position information and draw an incremental map on some of known or absolutely unknown environment.In this paper,the mobile robot platform is Dr Robot X80Pro,which is produced by Dr Robot Company.The robot with some sensing module,and add a URG-04LX laser lidar produced by HOKUYO,aimed to receiving the position and detecting the environment.This paper has completed the work as follows:Firstly,the Extended Kalman Filter algorithm and Particle Filter algorithm are derived in this paper,and had a simulation experiment.And take the measure of simultaneous localization and mapping in the robot operating system.Secondly,defined the mobile robot coordinate system,established the motion model of mobile robot and the observation model of the sensor.The local map building,mobile robot localization,data association and global map building are carried out in this coordinate system.Thirdly,this paper discussed two mobile robot simultaneous localization and mapping methods in detail.According to the requirements,programmed and simulated the Extended Kalman Filter and Particle Filter on Matlab.Finally,realized the aim to simultaneous localization and mapping on the robot operating system.