Research on ROS Service Robot Based on Multi-sensor Fusion SLAM
In order to improve the accuracy of autonomous navigation,Jetson Nano is used as the control platform,this research integrates simultaneous localization and mapping(SLAM)with path planning algorithms,amalgamating wheel odometry,LiDAR,and IMU sensor data to achieve accurate single and multi-point autonomous navigation.Firstly,ROS robot operating system is utilized to establish an autonomous navigation framework.The cartographer algorithm based on graph optimization is employed for environment map construction and robot pose estimation.Global path planning is conducted using the A* algorithm,while the g2o-optimized timed elastic band(TEB)algorithm is adopted for local path planning during abrupt environmental changes.Experimental findings demonstrate the superior mapping efficiency of the graph-based Cartographer algorithm compared to the commonly used particle filter-based Gmapping algorithm.Additionally,the g2o-optimized TEB algorithm effectively circumvents issues associated with robot entrapment during local path planning under the dynamic window approach(DWA),thus enhancing the precision of both intelligent robot mapping and path planning endeavors.
intelligent robotrobot operating system(ROS)simultaneous localization and mapping(SLAM)path planninglidar
万方数据
维普
