Indoor Localization And Path Planning Of Mecanum Wheel Mobile Robot

With the development of artificial intelligence and sensor technology,mobile robots are being applied in warehousing,home services,education and scientific research and other fields more and more widely.Indoor localization and path planning are important foundations for mobile robots to be applied in specific fields.For indoor scenes with relatively small space,the mobile robot with the Mecanum wheels can move in all directions without restriction,and has better maneuverability and flexibility.Therefore,the indoor localization and path planning of mecanum wheel mobile robot are of great significance for the application of mobile robots in indoor scenes.The main work of this thesis is as follows:First,the Mecanum wheel robot chassis is built,and we analyze the kinematic model and track calculation principle of the Mecanum wheel chassis.Based on this,the Mecanum wheel chassis control system is designed using the STM32 single-chip microcomputer as the robot chassis controller,which is used to execute the control instructions sent by the navigation system.In terms of indoor map construction and localization,the principle of Gmapping algorithm based on SLAM(simultaneous localization and mapping)is introduced,and we establish a grid map of the experimental site using this algorithm.Then the UWB positioning algorithm and adaptive Monte Carlo positioning algorithm are introduced.Aiming at the shortcomings of traditional adaptive Monte Carlo positioning algorithm,this thesis proposes an improved adaptive Monte Carlo positioning scheme that integrates UWB positioning information.Experiments have verified that the UWB positioning information improves the accuracy of adaptive Monte Carlo positioning,and can quickly restore accurate positioning in the robot kidnapping scene.For UWB positioning,after combining with adaptive Monte Carlo positioning,more accurate positioning results can be obtained when the UWB signal is blocked by obstacles,which improves the stability of positioning.In terms of path planning,A* global path planning algorithm is introduced,and an improved A* multi-robot path planning algorithm is proposed for the scene of multirobot cooperative work.This algorithm considers the path information already planned by other robots when the robot is planning the path,for planning a path that does not conflict with other robots.Simulation experiments prove that compared with the traditional A* algorithm,this algorithm can effectively avoid multiple robot path conflicts.Then we introduce the principle of Timed Elastic Band algorithm and test the effect of obstacle avoidance in the simulation environment.Finally,a navigation experiment platform is built on the basis of indoor localization and path planning research,and the static obstacles avoidance navigation experiment and the dynamic obstacles avoidance navigation experiment are carried out in real scenes.The experiments show that under the control of the navigation system,the robot can avoid obstacles and reach the target point smoothly,which verifies the effectiveness of the indoor localization and path planning research of this thesis in the navigation task.