Research On Environment Map Building And Navigation Method Of Mobile Robot

Map construction and navigation has always been the focus and difficulty in mobile robot technology research.In the process of map construction and navigation,sensors are usually needed to realize the robot’s perception and interaction with the surrounding environment.The self positioning information of internal sensors and the observation information of external sensors are very important for mobile robots.However,due to the influence of uncertain factors such as complex environment and sensor noise,it is often difficult for mobile robots to build accurate maps and realize real-time obstacle avoidance.In order to improve the navigation accuracy and anti-interference ability of mobile robot,This thesis designs a framework for an autonomous navigation robot system based on LIDAR as the main sensor,and investigates the methods of map construction and path planning.The main contents include:Based on the mobile robot ROS operating system,the robot odometer error model,LIDAR sensor model and beam measurement model are established respectively.According to the specific task requirements of autonomous navigation robot,the navigation system scheme of mobile robot is formulated.Aiming at the problem of large linearization error in the map building process of Fast SLAM algorithm based on Rao-Blackwellised Particle Filter,modified iterative extended Kalman filter Fast SLAM algorithm based on Newton iteration is proposed and applied to the map construction process of mobile robot,so as to improve the map construction accuracy of robot.The simulation results show that when the odometer data of the robot is valid,the algorithm can get the environment map with high accuracy and consistency.In order to solve the problems of large storage,excessive redundant nodes and inflection points of paths,unsmooth track in the traditional path planning algorithm,this thesis proposes an improved A* algorithm based on filtering extended neighborhood and extracting key nodes,and the algorithm is used to plan the global path on the environment map with known obstacles;Further,In order to ensure the safe operation of mobile robots,combining the improved A* algorithm with the dynamic window approach,the local path planning problem in the unknown environment of dynamic obstacles is studied.The simulation results show that the proposed path planning method is practical in dynamic grid environment map.