Radiometric Quality Assessment of Video Sequences Acquired from UAV Photogrammetric Systems

2017 ◽  
Author(s):  
Damian Wierzbicki ◽  
Anna Fryskowska
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Video Stream ◽  
Video Data ◽  
Video Sequences ◽  
Wide Field ◽  
Sensing Applications ◽  
Aerial Vehicles ◽  
High Resolution Imagery ◽  
Low Altitude ◽  
Imagery Data

The issue of imagery data collection and its implementation in photogrammetric studies with the use of unmanned aerial vehicles is still valid and provides a wide field of research in the creation of new and expansion of existing solutions. It is particularly important to increase the accuracy of photogrammetric products. These days low altitude unmanned aerial vehicles are being used more and more often in photogrammetric applications. Compact digital cameras had acquired single, high-resolution imagery. Data obtained from low altitudes were often (and still are) used in mapping and 3D modelling. Due to the low costs of flights of UAV systems in comparison with traditional flights, applications of such platforms are also attractive for many remote sensing applications. However, due to the use of non-metric video cameras, one of the main problems when trying to automate the video data processing, is the video sequences’ relatively poor radiometric quality. The article addresses the issue of assessing the quality of the video imagery acquired from a low altitude UAV platform. The Authors presented quality Indicators dedicated to UAV video sequences. The method is based on the analysis of the video stream, obtained in the different weather and lighting conditions. As a result of the research, an objective quality index for video acquired from low altitudes was determined.

scholarly journals Efficient Reactive Obstacle Avoidance Using Spirals for Escape

Drones ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 51
Author(s):  
Fábio Azevedo ◽  
Jaime S. Cardoso ◽  
André Ferreira ◽  
Tiago Fernandes ◽  
Miguel Moreira ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Mobile Robotics ◽  
Point Clouds ◽  
Depth Camera ◽  
Main Task ◽  
Robust Method ◽  
Aerial Vehicles ◽  
Correct Execution ◽  
Low Altitude ◽  
High Degree

The usage of unmanned aerial vehicles (UAV) has increased in recent years and new application scenarios have emerged. Some of them involve tasks that require a high degree of autonomy, leading to increasingly complex systems. In order for a robot to be autonomous, it requires appropriate perception sensors that interpret the environment and enable the correct execution of the main task of mobile robotics: navigation. In the case of UAVs, flying at low altitude greatly increases the probability of encountering obstacles, so they need a fast, simple, and robust method of collision avoidance. This work covers the problem of navigation in unknown scenarios by implementing a simple, yet robust, environment-reactive approach. The implementation is done with both CPU and GPU map representations to allow wider coverage of possible applications. This method searches for obstacles that cross a cylindrical safety volume, and selects an escape point from a spiral for avoiding the obstacle. The algorithm is able to successfully navigate in complex scenarios, using both a high and low-power computer, typically found aboard UAVs, relying only on a depth camera with a limited FOV and range. Depending on the configuration, the algorithm can process point clouds at nearly 40 Hz in Jetson Nano, while checking for threats at 10 kHz. Some preliminary tests were conducted with real-world scenarios, showing both the advantages and limitations of CPU and GPU-based methodologies.

scholarly journals Development of Non Expensive Technologies for Precise Maneuvering of Completely Autonomous Unmanned Aerial Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 391
Author(s):  
Luca Bigazzi ◽  
Stefano Gherardini ◽  
Giacomo Innocenti ◽  
Michele Basso
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Degrees Of Freedom ◽  
Vision System ◽  
Video Stream ◽  
Measurement Unit ◽  
Absolute Position ◽  
Light Load ◽  
Aerial Vehicles ◽  
Angular Velocities ◽  
Custom Hardware

In this paper, solutions for precise maneuvering of an autonomous small (e.g., 350-class) Unmanned Aerial Vehicles (UAVs) are designed and implemented from smart modifications of non expensive mass market technologies. The considered class of vehicles suffers from light load, and, therefore, only a limited amount of sensors and computing devices can be installed on-board. Then, to make the prototype capable of moving autonomously along a fixed trajectory, a “cyber-pilot”, able on demand to replace the human operator, has been implemented on an embedded control board. This cyber-pilot overrides the commands thanks to a custom hardware signal mixer. The drone is able to localize itself in the environment without ground assistance by using a camera possibly mounted on a 3 Degrees Of Freedom (DOF) gimbal suspension. A computer vision system elaborates the video stream pointing out land markers with known absolute position and orientation. This information is fused with accelerations from a 6-DOF Inertial Measurement Unit (IMU) to generate a “virtual sensor” which provides refined estimates of the pose, the absolute position, the speed and the angular velocities of the drone. Due to the importance of this sensor, several fusion strategies have been investigated. The resulting data are, finally, fed to a control algorithm featuring a number of uncoupled digital PID controllers which work to bring to zero the displacement from the desired trajectory.

scholarly journals Internet of Unmanned Aerial Vehicles—A Multilayer Low-Altitude Airspace Model for Distributed UAV Traffic Management

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4779 ◽  
Author(s):  
Nader S. Labib ◽  
Grégoire Danoy ◽  
Jedrzej Musial ◽  
Matthias R. Brust ◽  
Pascal Bouvry
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Traffic Management ◽  
Complex Problem ◽  
Experimental Simulation ◽  
Aerial Vehicles ◽  
Safe Management ◽  
Wide Range ◽  
Abstract Level ◽  
Low Altitude ◽  
New Research

The rapid adoption of Internet of Things (IoT) has encouraged the integration of new connected devices such as Unmanned Aerial Vehicles (UAVs) to the ubiquitous network. UAVs promise a pragmatic solution to the limitations of existing terrestrial IoT infrastructure as well as bring new means of delivering IoT services through a wide range of applications. Owning to their potential, UAVs are expected to soon dominate the low-altitude airspace over populated cities. This introduces new research challenges such as the safe management of UAVs operation under high traffic demands. This paper proposes a novel way of structuring the uncontrolled, low-altitude airspace, with the aim of addressing the complex problem of UAV traffic management at an abstract level. The work, hence, introduces a model of the airspace as a weighted multilayer network of nodes and airways and presents a set of experimental simulation results using three UAV traffic management heuristics.

scholarly journals Mapping of land cover with open‐source software and ultra‐high‐resolution imagery acquired with unmanned aerial vehicles

2020 ◽  
Vol 6 (4) ◽  
pp. 487-497 ◽  
Author(s):  
Ned Horning ◽  
Erica Fleishman ◽  
Peter J. Ersts ◽  
Frank A. Fogarty ◽  
Martha Wohlfeil Zillig
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Unmanned Aerial Vehicles ◽  
Open Source ◽  
Open Source Software ◽  
Aerial Vehicles ◽  
High Resolution Imagery

scholarly journals Spatial resolution of unmanned aerial vehicles acquired imagery as a result of different processing conditions

2021 ◽  
Vol 67 (3) ◽  
pp. 148-154
Author(s):  
Jaroslav Kubišta ◽  
Peter Surový
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Spatial Resolution ◽  
Light Condition ◽  
Weather Conditions ◽  
Flight Speed ◽  
Lighting Conditions ◽  
Aerial Vehicles ◽  
Flight Height ◽  
The Impact ◽  
Imagery Data

Abstract Increasing availability of Unmanned aerial vehicles (UAV) and different software for processing of UAV imagery data brings new possibilities for on-demand monitoring of environment, making it accessible to broader spectra of professionals with variable expertise in image processing and analysis. This brings also new questions related to imagery quality standards. One of important characteristics of imagery is its spatial resolution as it directly impacts the results of object recognition and further imagery processing. This study aims at identifying relationship between spatial resolution of UAV acquired imagery and variables of imagery acquiring conditions, especially UAV flight height, flight speed and lighting conditions. All of these characteristics has been proved as significantly influencing spatial resolution quality and all subsequent data based on this imagery. Higher flight height as well as flight speed brings lower spatial resolution, whereas better lighting conditions lead to better spatial resolution of imagery. In this article we conducted a study testing various heights, flight speeds and light conditions and tested the impact of these parameters on Ground Resolved Distance (GRD). We proved that from among the variables, height is the most significant factor, second position is speed and finally the light condition. All of these factors could be relevant for instance in implementation of UAV in forestry sector, where imagery data must be often collected in diverse terrain conditions and/or complex stand (especially vertical) structure, as well as different weather conditions.

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