Three-Dimensional Mapping of Indoor and Outdoor Environment Using LIO-SAM

This paper uses Velodyne Puck (VLP-16) 3D lidar sensor and Xsens MTI-G-700 to get inertial measurement unit (IMU) data to build a three-dimensional mapping of the indoor and outdoor environment and to visualize the constructed map using Lidar Inertia Odometry via Smoothing and Mapping (LIO-SAM) algorithm. The lidar sensor, Velodyne Puck (VLP-16) is used for obstacle detection of the environment and forms a three-dimensional point cloud, while Xsens MTI-G-700 is used to perform point cloud deskew. We have tested both indoor and outdoor environment experimentally and obtain the three-dimensional map of the environment and visualize it on Robot Operating System Visualization (Rviz) tool. The robot setup is teleoperated twice, once from its starting position to its end position and then move the robot back again to its initial position during the indoor mapping experiment, and moving the robot once during the outdoor mapping experiment. The experimental result shows that the system can create a compatible 3D mapping with the detailed information of the objects of the real environment.