| dc.description.abstract | The main objective of this thesis is to design an unmanned aerial vehicle (UAV) equipped with a GPS system and a monocular camera for constructing point clouds of large object scenes. After capturing the point cloud data, the system filters and corrects the objects, generates navigation points, path planning and object defect detection. The thesis aims to address major problem including navigation points transformation, UAV pose designed and defining the UAV′s viewpoint. This research extends and improves upon existing UAV-based visual localization for large object detection, making it applicable to open spaces such as statues, cars ,rooftop or water tanks. The ultimate goal is to enhance performance in outdoor environments.
The contributions of this thesis include filtering the point cloud to identify primary target objects, designing navigation points, path planning and coordinate transformation of navigation points combined with the UAV′s viewpoint for object inspection. Using GPS combined with a barometer compensation to improved the UAV′s stability and flight endurance that during outdoor flights.
The experimental process is as follows: First, manual flight that using Althold or Loiter mode for circling. Point cloud scenes will built by processing RGB images with GPS EXIF data through OpenSfM. RANSAC is applied to process the ground data, and we propose a method to extend the ground thickness to reduce outliers. DBSCAN filters and cluster the target objects and PCA transforms them to an ideal navigation coordinate system. After obtaining the target object, navigation points are generated using the method proposed in this thesis. At the same time overlapping navigation points created by sharp angles are solved and filtered with centroid algorithm and the Traveling Salesman Problem (TSP) is solved by Simulated Annealing (SA) combined with a Greedy Algorithm. Additionally, Intrinsic Shape Signatures (ISS) are used to obtain the object′s shape features that define the drone′s viewpoint and orientation.After the path planning, the data is uploaded to the UAV′s offboard control computer, where MAVROS is used to control peripheral devices such as altitude trending analysis, height compensation, object circling inspections, and gimbal control. Finally, during the object circling inspection, images are processed using YOLOv8 for defect detection. | en_US |