This paper proposes micro-ROS-based mobile robot system development and 2D mapping. Micro-ROS uses the micro-XRCE-DDS middleware to communicate with ROS2 in an extremely resource-constrained microcontroller environment. The mobile robot control system adopts a layered control method. The x64 PC equipped with Ubuntu ROS foxy is used as the main control platform, the olimex-stm32-E407 equipped with micro-ROS is used as the motion control layer, and the stm32F103 microcontroller is the underlying driver core. The forward and inverse kinematic equations are obtained through the analysis of the robot kinematics model. Through the interaction between the ROS2 nodes in the micro-ROS environment and the ROS2 nodes on the PC side, the cartographer algorithm is used to verify the effectiveness of the micro-ROS-based mobile robot system.
For mobile robots in uncertain and complex environments, a single sensor obtains a single set of environmental information, creates maps with low accuracy, is easily disturbed by external factors, and easily collides with obstacles in the navigation process. In this paper, we propose a depth camera and LiDAR fusion map building method, which firstly collects data using the LiDAR and depth camera on board the mobile robot, and then preprocesses the collected radar data and depth data and builds a 2D local environment map using RTAB-MAP algorithm. Finally, the local maps are fused using a voxel filter to stitch together a complete global map to complete the map construction. Experimental validation on a ROS-based mobile robot platform shows that the map built using multi-sensor fusion is more complete, presenting more comprehensive environmental information and laying the foundation for subsequent navigation.
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