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Title: | 3D point clouds terrain mapping system using lidar on UAV drone | Authors: | Le Thanh Vu Tru | Keywords: | LiDAR technology;Direct geo-referencing;Kalman Filter;Real-time kinematic | Issue Date: | 2023 | Abstract: | This thesis delves into the development and integration of a georeferenced point cloud generation system, centering on the Velodyne VLP-16 LiDAR unit mounted on a UAV platform, specifically the DJI Matrice M200. The objective is to create a LAS-formatted point cloud dataset adhering to specified standards. Components, including a Raspberry Pi 4, LiDAR sensor, IMU, and GPS sensor, contribute to autonomous data gathering during UAV surveys. Challenges such as time synchronization, recalibration, and error identification are addressed to ensure a cohesive hardware and software system. The Robotic Operating System (ROS) facilitates data collection during flight missions, and accuracy is verified through comparisons with reference points. The methodology encompasses the intricacies of direct geo-referencing for 3D point clouds, covering data collection using remote sensing techniques, sensor integration, and transformation of sensor-centric to geographical coordinates through sensor fusion and calibration. A topographic 3D point cloud map is generated, validated through comparative analyses with photogrammetric survey topographic maps. The findings showcase the LiDAR system's exceptional spatial attribute capture, with a maximal error of 3.75 meters and an RMSE of 1.85 meters. The georeferenced point cloud exhibits an RMSE of 0.92 meters, demonstrating high precision and accuracy. This research contributes significant insights into georeferenced LiDAR-based point cloud generation systems, providing a foundation for enhanced spatial mapping and analysis applications |
URI(1): | https://epub.vgu.edu.vn/handle/dlibvgu/1780 |
Appears in Collections: | Electrical Engineering and Information Technology (EEIT) Electrical Engineering and Information Technology (EEIT) |
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