Research On Indoor Positioning And Path Planning Technology Of Mobile Robot

With the rapid development of artificial intelligence and sensor technology,mobile robots are now widely used in industry,agriculture,education,national defense and other fields.In practical applications,how to estimate the pose of the robot through the sensor equipment carried by the robot itself,so as to achieve autonomous navigation has become an important scientific and technological issue.Therefore,the thesis focuses on the indoor localization and path planning technology of mobile robots.The main contents of the thesis is as follows :Firstly,the mobile robot with autonomous localiztion,path planning and dynamic obstacle avoidance is studied and built.The robot system model is established,and the coordinate system,environment map model,odometer motion model and lidar ranging model of the robot are introduced in detail.The hardware selection of mobile robot is designed and developed,and the software framework based on ROS robot operating system is designed,which provides a platform for subsequent algorithm research and experimental verification.Secondly,the mobile robot mapping and indoor positioning algorithm are studied and analyzed.The laser lidar scanning environment information is used to construct the grid map,and the autonomous localization of the mobile robot in the grid map is completed.Through the study of adaptive Monte Carlo,which is widely used in positioning algorithm,it is found that the particle update based on motion model in adaptive Monte Carlo algorithm will affect the localization accuracy.Therefore,using an unscented Kalman filter algorithm to fuse the odometer data and the IMU data,and the fused pose is updated as the motion model in the adaptive Monte Carlo algorithm.Experiments show that the fused algorithm has higher localizaton accuracy.Based on the mapping and localization of mobile robots,the path planning algorithm of mobile robots is studied,and the basic principles of A* algorithm and dynamic window method are introduced.To solve the problems of multiple path redundancy points,many inflection points and low smoothness of the global path planned by the traditional A*algorithm in practical applications,an improvement is proposed to improve the A* algorithm.The evaluation function in the A* algorithm introduces the objective weight factor,and performs corner optimization and path smoothing on the generated global path.The simulation results show that the improved A* algorithm is more efficient,and the dynamic window method can effectively realize dynamic obstacle avoidance.Finally,the mobile robot is used as the experimental platform,and the mapping,localization and path planning experiments are carried out using the research algorithm in the real scene.The effectiveness of the indoor localization algorithm and path planning algorithm is verified.