Solution For Unmanned Aerial Vehicle Research Articles

Contour Mission Flight Planning of UAV for Photogrammetric in Hillside Areas

Unmanned Aerial Vehicle (UAV) photogrammetry is an effective method for acquiring terrain information. However, in hillside areas, the terrain is complex, and the altitude varies greatly. The mission flight is planned by using equal altitude; in the actual shooting, the geometry and resolution of the pixel within the same image or between adjacent images will be inconsistent due to the different shooting distances. The number and accuracy of point clouds are affected. We propose a contour mission flight plan method, which involves designing flight plans based on the existing digital elevation model (DEM) and the desired flight altitude. This method for aerial photography is more effective in maintaining a consistent ground shooting distance during image capture. Experiments were conducted using a simulated DEM and the undulating terrain of the Kaohsiung Liugui area in Taiwan to verify the effect of contour mission flight planning in the hillside area. The results show that, due to the significant variation of terrain in the hillside area, the use of a contour mission flight plan for aerial photography can be more consistent with the originally planned altitude but requires more planning and operating time. The minor height difference, higher overlap, and improved accuracy of the results show that contour mission planning can provide a suitable solution for UAVs in hillside areas.

3-D Positioning Method for Anonymous UAV Based on Bistatic Polarized MIMO Radar

The Angle-of-Arrival (AoA)-based approach is an appealing solution for unmanned aerial vehicle (UAV) positioning, and has received significant interest recently. In this article, we propose a novel framework for UAV three-dimensional (3-D) positioning, the core of which is to measure the two-dimensional (2-D) Angle-of-Departure (2D-AoD) and 2D-AoA via a bistatic multiple-input multiple-output (MIMO) radar. Unlike the existing positioning architectures, the MIMO radar is equipped with polarized array antennas. An estimator based on the parallel factor (PARAFAC) decomposition is developed. It first obtains the direction matrices via performing the PARAFAC decomposition of the array data. Thereafter, the rotational invariance characteristic is utilized to form a normalized polarization response vector, from which the 2D-AoD, 2D-AoA, and polarization status of the UAVs are achieved via incorporating the vector cross-product method and the least squares (LSs) technique. Finally, the 3-D positions of the UAVs are easily calculated via the location relationship between the 2D-AoD, 2D-AoA, and the coordinates of transmitting/receiving (Tx/Rx) array. The proposed framework is computationally friendly, and is capable of positioning anonymous UAV. Moreover, it is insensitive to the geometry of the Tx/Rx array, indicating that the proposed framework supports configurable Tx/Rx antennas. Simulation results are provided to verify our theoretical advantages.

Accuracy Assessment of UAV for Cadastral Application

This study aims to produce accurate geospatial 3D data from unmanned aerial vehicle (UAV) images. An image of approx. 1 km2 area of the Banepa-10, Kabhrepalanchok district was captured using a DJI Mavic Pro drone. Pix4dmapper programs were used to generate the solution. The horizontal and vertical accuracies of the obtained UAV solution were computed by comparing the coordinates of 5 Ground Control Points (GCPs) with coordinates measured using the static DGPS observation method. The root mean square error (RMSE) was calculated during geo-referencing of Orthomosaic and obtained a value of 0.006.Mainly, three comparisons were made for parcels digitized from the Orthomosaic image w.r.t to Total Station and Tape measurement ; Area, Perimeter and Centroid Position. Cadastral survey using Total station, UAV and Tape measurement were confirmed to be comparable in terms of accuracy, completeness, and expenditure of time. From the result of this study, the area as well perimeter of parcels obtained from georeferenced orthorectified UAV image seems to be closer with the area as well as perimeter from total station survey compared to those obtained from tape measurement. If the area is pre-demarcated and clearly visible in Orthomosaic image, then information can efficiently be gained. Some ambiguity could be seen in the comparison of digitized parcels whose boundary information was not clear.

LiDAR-odometry based UAV pose estimation in young forest environment

In this study, we propose a real-time pose estimation solution for Unmanned Aerial Vehicle in a seedling pine forest environment. Our method uses graph-based approach to fuse data from an onboard IMU sensors, a GNSS receiver and a 3D LiDAR. Features are detected from every LiDAR scan. A local map is built from the detected features and used to compute the LiDAR odometry in real time for the incoming scans. In order to obtain a robust estimate of the state of the vehicle, the noise covariance of the LiDAR odometry is updated at each iteration using the fitness score of the LiDAR. The proposed solution provides promising trajectory and velocity estimates even in GNSS denied scenario. Both the local and global consistencies of the estimated trajectory are encouraging.

2-D UAV navigation solution with LIDAR sensor under GPS-denied environment

Unmanned aerial vehicle (UAV) is widely used by many industries these days such as militaries, agriculture, and surveillance. However, one of the main challenges of UAV is navigating through an environment where global positioning system (GPS) is being denied. The main purpose of this paper is to find a solution for UAV to be able to navigate in a GPS denied surrounding without affecting the drone flight performance. There are two ways to overcome these challenges such as using visual odometry (VO) or by using simultaneous localization and mapping (SLAM). However, VO has a drawback because camera sensors require good lighting which will affect the performance of the UAV when it is navigating through a low light intensity environment. Hence, in this paper 2-D SLAM will be use as a solution to help UAV to navigate under a GPS-denied environment with the help of a light detection and ranging (LIDAR) sensor which known as a LIDAR-based SLAM. This is because SLAM can help UAVs to localize itself and map the surrounding of the environment. The concept and idea of this paper will be fully simulated using MATLAB, where the drone navigation will be simulated in MATLAB to extract LIDAR data and to use the LIDAR data to carry out SLAM via pose graph optimization. Besides, the contribution to this research work has also identified that in pose graph optimization, the loop closure threshold and loop closure radius play an important role. The loop closure threshold can affect the accuracy of the trajectory of the drone and the accuracy of mapping the environment as compared to ground truth. On the other hand, the loop closure search radius can increase the processing speed of obtaining the data via pose graph optimization. The main contribution to this research work is shown that the processing speed can increase up to 45 % and the accuracy of the trajectory of the drone and the mapped surrounding is quite accurate as compared to ground truth.

Unmanned Aerial Vehicle Recognition of Maritime Small-Target Based on Biological Eagle-Eye Vision Adaptation Mechanism

Inspired by the background adaptive mechanism of eagle vision in different hunting environment, a biological eagle-eye vision adaptation mechanism algorithm is proposed for unmanned aerial vehicle (UAV) to detect the long-distance maritime small target in complex and changeable sea environment. First, the various environment adjustment abilities are summarized according to the physiological structures and characteristics of eagle vision. Second, the mathematical models of glaring adaptation, dim adaptation, color adaptation, and the background adaptation are established based on the background adaptation mechanisms of eagle vision. Last but not least, our proposed biological eagle-eye vision adaptation method and other five comparative experiments are implemented in different scenes, such as dazzling, cloudy, dusk, etc. The results of various evaluation indices show that the information of maritime small target is retained satisfactorily and the background of sea or sky is restrained effectively by the proposed algorithm. The maritime small target detection algorithm can be used for the vision system of UAV operating on the sea. It provides a feasible solution for UAV's remote vision autonomous navigation in changeable sea environment.

Accuracy Assessment of Low-Cost Unmanned Aerial Vehicle (UAV) Photogrammetry

This study aims to produce accurate geospatial 3D data from unmanned aerial vehicle (UAV) images. An image of a ≈ 0.05 km2 area of the Najran University campus in Najran, Saudi Arabia, was captured using a DJI Mavic Pro Platinum drone. Agisoft Metashape and Pix4dmapper programs were used to generate the solution. The horizontal and vertical accuracies of the obtained UAV solution were computed by comparing the coordinates of 21 ground control points (GCPs) with coordinates measured using the RTK GPS method. The accuracy of the four different GCP configurations was evaluated using both software packages. The root mean square error (RMSE) was calculated for some checkpoints. The generated model achieved the 2015 ASPRS accuracy standards for digital geospatial data, while horizontal RMSE values were 4–6 cm and vertical accuracy was 5–6 cm. The horizontal and vertical RMSE values were twice and three times the GSD, respectively.

Design of UAV wireless power transmission system based on coupling coil structure optimization

With the development of unmanned aerial vehicle (UAV), it has been used in many fields, such as aerial photography, military, and transportation. However, it is a challenge for charging due to its short battery life. Wireless charging has been considered as a good UAV solution. In this paper, we proposed a wireless power transmission system (WPT) through inductive coupling and analyzed the power efficiency of the inductive coupling. The WPT included a charging station, which can provide energy through an induction coil array, and a portable energy receiving device mounted on the base of the UAV. Moreover, the power efficiency was analyzed though the equivalent circuit of WPT and the mathematical model of the power efficiency was established. The results showed that the WPT can transfer energy to UAV with high power efficiency within a 30 mm lateral displacement range.