Research On Navigation System Of Mobile Robot Based On Laser Sensor

Autonomous navigation technology is the key technology in the field of mobile robot.It usually includes two modules: simultaneous positioning and mapping(SLAM)and path planning.SLAM is the premise and guarantee of mobile robot path planning for mobile robot.In the SLAM system,due to the influence of weather,illumination and other environmental factors,lidar sensors and inertial navigation unit(IMU)are usually used as the main input information for positioning and mapping.Based on the above background,this paper studies the navigation system of mobile robot based on laser sensor.The main work is as follows:Firstly,the environment information of mobile robot navigation system is collected and expressed.According to different types of sensors,different methods are used to collect data,and the data collected by IMU are used for attitude calculation and coordinate system conversion.At the same time,different expression methods of environmental information data in SLAM system and their advantages and disadvantages are explained.Secondly,aiming at the problem of mobile robot SLAM,according to the different methods of state estimation of mobile robot in SLAM algorithm,the working principle of SLAM algorithm based on probability model and SLAM algorithm based on non probability model is theoretically deduced,and in the small practical environment,Gmapping SLAM based on probability model and Cartographer based on non probability model are analyzed the SLAM algorithm is compared in the accuracy and real-time.The experimental results show that the Cartographer SLAM algorithm takes longer to build a graph,but its accuracy is higher.However,when Cartographer SLAM algorithm is used for map building in large scenes,due to the drift of IMU data,the quality of local map building is poor,and it can not achieve closed loop.To solve this problem,this paper uses correlation scan matching method to optimize the pose estimation method in Cartographer SLAM algorithm and eliminate the influence of data drift.The experimental results show that this method can effectively solve the problem of pose estimation under the data drift of IMU.The quality of map building is improved obviously.When the mobile robot moves to the previous position,the map can be closed loop.Finally,aiming at the path planning problem of mobile robot based on the known surrounding environment information,this paper uses the A* algorithm under the framework of move base navigation package as the global path planning algorithm,and the dynamic window method as the local path planning algorithm to navigate and avoid obstacles for mobile robot.The simulation results show that this method can realize the efficient path planning of mobile robot in the constructed map.