Unmanned Aerial Vehicle

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Ismail Elkhrachy - One of the best experts on this subject based on the ideXlab platform.

  • accuracy assessment of low cost Unmanned Aerial Vehicle uav photogrammetry
    alexandria engineering journal, 2021
    Co-Authors: Ismail Elkhrachy

    Abstract 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.

Lincheng Shen - One of the best experts on this subject based on the ideXlab platform.

  • information geometry based action decision making for target tracking by fixed wing Unmanned Aerial Vehicle from algorithm design to theory analysis
    International Journal of Advanced Robotic Systems, 2018
    Co-Authors: Yunyun Zhao, Xiangke Wang, Yirui Cong, Lincheng Shen

    In this article, we study the ground moving target tracking problem for a fixed-wing Unmanned Aerial Vehicle equipped with a radar. This problem is formulated in a partially observable Markov proce...

  • control and flight test of a tilt rotor Unmanned Aerial Vehicle
    International Journal of Advanced Robotic Systems, 2017
    Co-Authors: Chao Chen, Daibing Zhang, Jiyang Zhang, Lincheng Shen

    Tilt-rotor Unmanned Aerial Vehicles have attracted increasing attention due to their ability to perform vertical take-off and landing and their high-speed cruising abilities, thereby presenting broad application prospects. Considering portability and applications in tasks characterized by constrained or small scope areas, this article presents a compact tricopter configuration tilt-rotor Unmanned Aerial Vehicle with full modes of flight from the rotor mode to the fixed-wing mode and vice versa. The unique multiple modes make the tilt-rotor Unmanned Aerial Vehicle a multi-input multi-output, non-affine, multi-channel cross coupling, and nonlinear system. Considering these characteristics, a control allocation method is designed to make the controller adaptive to the full modes of flight. To reduce the cost, the accurate dynamic model of the tilt-rotor Unmanned Aerial Vehicle is not obtained, so a full-mode flight strategy is designed in view of this situation. An autonomous flight test was conducted, and t...

Shankar Sastry - One of the best experts on this subject based on the ideXlab platform.

  • a vision system for landing an Unmanned Aerial Vehicle
    International Conference on Robotics and Automation, 2001
    Co-Authors: C Sharp, O Shakernia, Shankar Sastry

    We present the design and implementation of a real-time computer vision system for a rotorcraft Unmanned Aerial Vehicle to land onto a known landing target. This vision system consists of customized software and off-the-shelf hardware which perform image processing, segmentation, feature point extraction, camera pan/tilt control, and motion estimation. We introduce the design of a landing target which significantly simplifies the computer vision tasks such as corner detection and correspondence matching. Customized algorithms are developed to allow for realtime computation at a frame rate of 30 Hz. Such algorithms include certain linear and nonlinear optimization schemes for model-based camera pose estimation. We present results from an actual flight test which show the vision-based state estimates are accurate to within 5 cm in each axis of translation, and 5 degrees in each axis of rotation, making vision a viable sensor to be placed in the control loop of a hierarchical flight management system.

Henri Eisenbeiss - One of the best experts on this subject based on the ideXlab platform.

    Heritage, 2004
    Co-Authors: Henri Eisenbeiss

    In the last years UAV (Unmanned Aerial Vehicle)-systems became relevant for applications in precision farming and in infrastructure maintenance, like road maintenance and dam surveillance. This paper gives an overview about UAV (Unmanned Aerial Vehicle) systems and their application for photogrammetric recording and documentation of cultural heritage. First the historical development of UAV systems and the definition of UAV-helicopters will be given. The advantages of a photogrammetric system on-board a model helicopter will be briefly discussed and compared to standard Aerial and terrestrial photogrammetry. UAVs are mostly low cost systems and flexible and therefore a suitable alternative solution compared to other mobile mapping systems. A mini UAV-system was used for photogrammetric image data acquisition near Palpa in Peru. A settlement from the 13th century AD, which was presumably used as a mine, was flown with a model helicopter. Based on the image data, an accurate 3D-model will be generated in the future. With an orthophoto and a DEM derived from Aerial images in a scale of 1:7 000, a flight planning was build up. The determined flying positions were implemented in the flight control system. Thus, the helicopter is able to fly to predefined pathpoints automatically. Tests in Switzerland and the flights in Pinchango Alto showed that using the built-in GPS/INS- and stabilization units of the flight control system, predefined positions could be reached exactly to acquire the images. The predicted strip crossings and flying height were kept accurately in the autonomous flying mode.

Gangbing Song - One of the best experts on this subject based on the ideXlab platform.