Research And Implementation Of Indoor Mobile Robot Navigation Technology Based On Multi-sensor Information Fusion

Navigation technology is an important part of the research field of mobile robots,and it is a necessary condition for realizing the autonomy and intelligence of mobile robots.This thesis focuses on the SLAM algorithm,autonomous positioning and path planning for the autonomous navigation of indoor mobile robots,and initially realizes the autonomous navigation of the robot.This thesis solves the problem of incomplete map information of single laser SLAM algorithm based on multi-sensor information fusion,and improves the effect of mobile robot autonomous positioning and path planning.The main research contents of this thesis are as follows:1.Research on autonomous mobile robot for indoor environments.According to the research content of this thesis,autonomous mobile robots satisfying the research needs are designed.The construction of the mobile robot hardware platform was completed,and the mobile robot software system was designed based on the open source robot operating system(ROS).The designed mobile robot is used as the verification platform of the related algorithm in this thesis,and the autonomous navigation of the mobile robot is realized.2.Aiming at the problem of incomplete map obstacle information constructed by single laser SLAM algorithm,a Multi-sensor information fusion SLAM algorithm is improved.The laser scanning data is integrated with the three-dimensional point cloud data to make the obstacle information in the map richer and more complete.The Kalman filter is used to fuse the odometer data with the observation data to achieve more accurate positioning.Closed-loop detection and graph optimization are used to eliminate cumulative errors of positioning and make the constructed map more accurate.3.Aiming at the problem of the ROS navigation package needs to artificially specify the initial pose of the mobile robot after starting the robot,a global positioning method of the mobile robots is proposed.Based on the Adaptive Monte Carlo Localization,the global positioning of the mobile robot at any position in the map is realized,which avoids the human intervention of the mobile robot and improves the autonomy of the mobile robot navigation.4.Aiming at the problem of the local path planning algorithm based on Dynamic Window Approach(DWA)requires a large number of sampling simulations,a local path planning algorithm based on dynamic window method is improved.This allows the mobile robot does not need to not perform sampling simulation when it encounters no dynamic obstacles,greatly reduces the computational complexity of the algorithm and ensures the dynamic obstacle avoidance capability of the mobile robot.