Research On Mobile Robot Navigation Positioning And Path Planning Technology

Mobile robots are widely used in e-commerce logistics,manufacturing and other social fields.The key technologies of mobile robot autonomous navigation include navigation positioning and path planning technology,but there are still problems of insufficient positioning accuracy and navigation ability.This paper studies the navigation positioning and path planning technology of wheeled mobile robot,in order to improve the robot navigation positioning accuracy and path planning ability,so as to improve the accuracy of robot navigation.Firstly,the local localization technology of robot is studied,the odometer model of mobile robot is analyzed and established,and the odometer error based on encoder information is corrected.A binocular vision odometer based on the feature point method is designed.Through the extended Kalman filter,the odometer information based on IMU and encoder information is fused to realize the local positioning of robot.The experiment shows that the fused positioning information is more accurate and reliable than the single sensor positioning information.Secondly,the global positioning technology of robot is studied,the principle of lidar ranging and the cause of motion distortion are analyzed,and the motion distortion of lidar is corrected by quadratic interpolation method.This paper analyzes the environment map construction algorithm,and uses cartographer algorithm to build the environment map.Based on the Adaptive Monte Carlo localization algorithm,the particle set motion is updated by the fusion of local localization information to improve the global localization accuracy.Then the robot path planning technology is studied,and a multi-objective path planning method is proposed.In order to solve the path planning problem of mobile robot traversing all target points with the shortest path in two-dimensional grid map,a path planning method based on heuristic information extended node a * algorithm and hybrid ant colony algorithm is proposed.Through the node expansion function based on heuristic information,the planning efficiency is improved.By adaptively adjusting pheromone volatilization factor of ant colony algorithm and crossover mutation operation with the optimal solution,the shortcoming that ant colony algorithm is easy to fall into local optimal solution is improved.The simulation results show that compared with a * algorithm,the search nodes of a *algorithm based on heuristic information expansion nodes are reduced by 13.18%;the optimal path and average path of hybrid ant colony algorithm are better than that of ant colony algorithm,and it is not easy to fall into the local optimal solution in the iterative process.The real-time path planning algorithm based on dynamic window method is used to control the robot motion.Finally,the robot coordinate system transformation is analyzed,the robot navigation process is designed,and the robot global positioning experiment,navigation experiment and multi-objective point path planning experiment are carried out in the real environment through the robot navigation experimental platform.The experimental data show that the positioning accuracy of the improved positioning algorithm is improved by about 30%compared with the Adaptive Monte Carlo algorithm,which is very important in the multi-objective path planning experiment The proposed algorithm can plan a short path.