Research Of Simultaneous Localization And Mapping Based On ROS For Guide Robot

In recent years the number of the visually handicapped is growing more and more in China. Therefore it's very necessary and urgent to research a guide tool named guide robot to assist the visually handicapped walk. The precondition of guide robot autonomous operation is to establish the environmental map and be able to complete the self-localization at any time in the environment. This process is called simultaneous localization and mapping. The research of the article is around the simultaneous localization and mapping.This paper is on the basis of the turtlebot2 which belong to the laboratory. In this paper develop a guide robot prototype which is controlled by the wireless controller and detect the environment by the laser range finder. In this paper, the software architecture is using the robot operating system. In this paper the research content includes four aspects. As follows:the construction of the guide robot experimental prototype; building the guide robot system model; the research of the guide robot SLAM algorithm with MATALB experiment simulation; the guide robot experiment and analysis in the real environmentFirstly, this paper completed the construction of the guide robot prototype. The turtlebot2 robot is using the laser range finder instead of the Kinect vision sensor. The laser range finder is used to be an external observation of the guide robot. At the same time the guide robot connects with the controller which is dual-mode, wireless, shaking force feedback. The guide robot is controlled by the controller. At the same time, under the ROS,the guide robot establishs the laser range finder node and handle node, ensure that the guide robot can communicate with each other between each node.Secondly, this paper researches the guide robot and analyzes the SLAM basic theory.Building the motion model of the guide robot; the observation model of the guide robot; the environment map model ect. In this process, in order to simplify the calculation, the motion model of guide robot is built by linear motion way.Then this paper researches the simultaneous localization and mapping algorithm of guide robot. This paper is based on the kalman filter and particle filter algorithm theory.According to all kinds of system models in the experiments process of SLAM put forward the EKF-SLAM algorithm based on Kalman Filter and the FastSLAM algorithm based on Particle Filter. And using MATLAB simulation software creates the simulation environment of the guide robot operation and doing the experiment simulation of the EKF-SLAM andFastSLAM respectively, then, analyzing the guide robot's position error of X direction, Y direction and course angle. After the experimental simulation and comparison analysis it is obvious that the FastSLAM cumulative error is smaller than the EKF-SLAM cumulative error under the same parameters.Finally, using the guide robot platform in this paper create the 2D map of the real environment. Analyzing the problems of the experiment, we can obtain a conclusion that the quality of map is related to the stability of the robot body, the complexity of the skid and the environment in the process of the robot.