Research On Robot Positioning And Navigation System Based On ROS

With the rapid development of science and technology,artificial intelligence and machine learning have been promoted and widely used as never before.At the same time,robotics technology has also been continuously expanded.Both the current service robots and underground detection robots are inseparable from localization and navigation functions,and Autonomous navigation has always been a hot and difficult point in robotics.Therefore,this paper studies the robot composition and navigation,analyzes the robot motion model,SLAM and path planning technology,and verifies the algorithm based on the ROS platform.The research content of this paper is as follows:1)This paper analyzes the domestic and foreign research status of robotics,and builds the overall layout of the robot according to the specific functions realized by the robot.Then,according to the layered thinking,the hardware structure of the robot is explained,and then the robot is introduced.The sensor components(bottom driver,Raspberry Pi development board,lidar,IMU)and robot operating system ROS and robot motion model.2)In view of the deviation and ambiguity in the construction of the environment map,this paper explores the SLAM technology of the robot.Based on the particle filter SLAM,mathematical analysis and formula derivation are used to optimize the proposal distribution and selective resampling,and simulate experiments.The analysis shows that the improved RBPF algorithm has high accuracy and real-time performance.It can build a good environment map for the current environment,and then analyze the mapping effect with the SLAM based on graph optimization.It is concluded that the algorithm consumes less resources and is easy to expand.application.3)Aiming at the collision or stagnation of the robot using a single navigation algorithm in path planning,a fusion algorithm is proposed.This paper first studied the Dijkstra and A*algorithms in the constructed map,and compared and analyzed the experimental data and tables.The results show that A*has a small amount of calculation and a short search time.And the A*algorithm has been improved and experimentally verified.The experiment shows that the improved A*algorithm is more efficient than the traditional A*algorithm in terms of path finding time and search nodes.Therefore,it is decided to use the A*algorithm as the global navigation algorithm.And then simulated the DWA in Matlab,and finally decided to combine the two algorithms as the robot's navigation algorithm.4)In this paper,the simulation environment of the robot is designed on the ROS experimental platform.At the same time,the RVIZ tool is used to observe the mapping and navigation process.Through algorithm experiments,the robot's mapping effect in the simulation environment and the real environment are verified.The mapping effect,as well as the navigation function in the simulation environment and the navigation function in the real environment.The experimental results show that the designed robot positioning and navigation system meets the performance requirements and can complete the autonomous navigation function of the robot.