Research And Implementation On SLAM And Navigation System Of Omnidirectional Mobile Robot Based On ROS

With the advent of Robot Operating System(ROS)and the development of artificial intelligence technology,mobile robots are widely used in various fields of production and life.Based on ROS,an omnidirectional mobile robot for indoor environment is designed,mainly including motion control,localization and mapping and navigation.Firstly,the omnidirectional mobile robot platform acquires environmental information by installing a lidar scanner and odometer sensor's components.The kinematics model of omnidirectional mobile robot is established,and the control strategy is proposed based on motion characteristics.Afterwards,the RBPF-SLAM algorithm and the improved RBPF-SLAM algorithm with enhanced proposed distribution and adaptive partial Gaussian resampling method are introduced.The gradient-degraded attitude fusion algorithm is adopted to reduce the error of map.Two indoor environments with different complexity are selected for experiments to research and design the SLAM system.Finally,the A*algorithm is selected as the global path planning algorithm,and the DWA algorithm is used as the local path planning algorithm.The autonomous navigation experiment and dynamic obstacle avoidance experiment are designed to research and design the omnidirectional mobile robot navigation system.An excellent control method for omnidirectional mobile robot is designed based on ROS.The improved RBPF-SLAM algorithm is used to improve the accuracy and efficiency of robot map construction.The combination of A*algorithm and DWA algorithm makes the omnidirectional mobile robot plan the best navigation path and realize the obstacle avoidance function.On this basis,a camera is equipped to finish the goal-following experiment.This combination verifies the feasibility of the design idea.