scholarly journals TOWARDS MORE EFFICIENT UAS DATA ACQUISITION: CAMERA AUTO MOUNT PIVOTING OBLIQUE SURVEY

2021 ◽  
Vol XLIII-B1-2021 ◽  
pp. 139-147
Author(s):  
I. S. G. Campos
Keyword(s):  
Field Experiments ◽  
Region Of Interest ◽  
Point Clouds ◽  
Ground Control ◽  
Unmanned Aerial Systems ◽  
Coverage Area ◽  
Check Points ◽  
Ground Control Station ◽  
Aerial Systems ◽  
Additional Hardware

Abstract. In this paper I present a new MAVLink command, enabling oblique aerial surveys, along with its implementation on the major open source flight stacks (PX4 and ArduPilot) and ground control station (QGroundControl). A key advantage of this approach is that it enables vehicles with a typical gimbaled camera to capture oblique photos in the same pass as nadir photos, without the need for heavier and more expensive alternatives that feature multiple cameras, at fixed angles in a rigid mount, thus are unsuitable for lightweight platforms. It also allows for flexibility in the configuration of the camera angles. The principle is quite simple, the command combines camera triggering with mount actuation in a synchronized cycle along the flight traverses through the region of interest. Oblique photos have also been shown to increase the accuracy of data and help filling holes in point clouds and related outputs of surveys with vertical components. To provide evidence of its benefits, I compare the results of several missions, in simulated and field experiments, flown with nadir only surveys versus oblique surveys, and different camera configurations. In both cases, ground control and check points were used to evaluate the accuracy of the surveys. The field experiments show the vehicle had to fly 44% less with the oblique survey to cover the same area as the nadir survey, which could translate in a 80% gain in efficiency in coverage area per flight. Furthermore, this new command is capable of enhancing functionality of Unmanned Aerial Systems (UASs) without any additional hardware, therefore its adoption should be straightforward.

scholarly journals Improving Human Ground Control Performance in Unmanned Aerial Systems

2021 ◽  
Vol 13 (8) ◽  
pp. 188
Author(s):  
Marianna Di Gregorio ◽  
Marco Romano ◽  
Monica Sebillo ◽  
Giuliana Vitiello ◽  
Angela Vozella
Keyword(s):  
Situation Awareness ◽  
Interface Design ◽  
Human Machine Interface ◽  
Ground Control ◽  
Entire Group ◽  
Unmanned Aerial Systems ◽  
Ground Control Station ◽  
Machine Interface ◽  
Team Situation Awareness ◽  
Aerial Systems

The use of Unmanned Aerial Systems, commonly called drones, is growing enormously today. Applications that can benefit from the use of fleets of drones and a related human–machine interface are emerging to ensure better performance and reliability. In particular, a fleet of drones can become a valuable tool for monitoring a wide area and transmitting relevant information to the ground control station. We present a human–machine interface for a Ground Control Station used to remotely operate a fleet of drones, in a collaborative setting, by a team of multiple operators. In such a collaborative setting, a major interface design challenge has been to maximize the Team Situation Awareness, shifting the focus from the individual operator to the entire group decision-makers. We were especially interested in testing the hypothesis that shared displays may improve the team situation awareness and hence the overall performance. The experimental study we present shows that there is no difference in performance between shared and non-shared displays. However, in trials when unexpected events occurred, teams using shared displays-maintained good performance whereas in teams using non-shared displays performance reduced. In particular, in case of unexpected situations, operators are able to safely bring more drones home, maintaining a higher level of team situational awareness.

scholarly journals Development of a Flexible and Expandable UTM Simulator Based on Open Sources and Platforms

Aerospace ◽  
2021 ◽  
Vol 8 (5) ◽  
pp. 133
Author(s):  
Sugjoon Yoon ◽  
Dongcho Shin ◽  
Younghoon Choi ◽  
Kyungtae Park
Keyword(s):  
Operating System ◽  
Field Study ◽  
Traffic Control ◽  
Traffic Management ◽  
Ground Control ◽  
Unmanned Aerial Systems ◽  
Present Design ◽  
Independent Process ◽  
Design Requirements ◽  
Aerial Systems

In order to study air traffic control of UAS’s (Unmanned Aerial Systems) in very low altitudes, the UTM (UAS Traffic Management) simulator has to be as flexible and expandable as other research simulators because relevant technologies and regulations are not matured enough at this stage. Available approaches using open sources and platforms are investigated to be used in the UTM simulator. The fundamental rationale for selection is availability of necessary resources to build a UTM simulator. Integration efforts to build a UTM simulator are elaborated, using Ardupilot, MavProxi, Cesium, and VWorld, which are selected from the thorough field study. Design requirements of a UTM simulator are determined by analyzing UTM services defined by NASA (National Aeronautics and Space Administration) and Eurocontrol. The UTM simulator, named eUTM, is composed of three components: UOS (UTM Operating System), UTM, and multiple GCSs (Ground Control Stations). GCSs are responsible for generation of flight paths of various UASs. UTM component copies functions of a real UTM such as monitoring and controlling air spaces. UOS provides simulation of environment such as weather, and controls the whole UTM simulator system. UOS also generates operation scenarios of UTM, and resides on the same UTM computer as an independent process. Two GCS simulators are connected to the UTM simulator in the present configuration, but the UTM simulator can be expanded to include up to 10 GCS simulators in the present design. In order to demonstrate the flexibility and expandability of eUTM simulator, several operation scenarios are realized and typical deconfliction scenarios among them are tested with a deconfliction algorithm. During the study, some limits are identified with applied open sources and platforms, which have to be resolved in order to obtain a flexible and expandable UTM simulator supporting relevant studies. Most of them are related to interfacing individual sources and platforms which use different program languages and communication drivers.

scholarly journals Accuracy of 3D Landscape Reconstruction without Ground Control Points Using Different UAS Platforms

Drones ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 13 ◽  
Author(s):  
Margaret Kalacska ◽  
Oliver Lucanus ◽  
J. Pablo Arroyo-Mora ◽  
Étienne Laliberté ◽  
Kathryn Elmer ◽  
...  
Keyword(s):  
Low Cost ◽  
Ground Control ◽  
Unmanned Aerial Systems ◽  
Control Points ◽  
Model Errors ◽  
Positional Accuracy ◽  
Ground Control Points ◽  
Digital Elevation ◽  
High Level ◽  
Aerial Systems

The rapid increase of low-cost consumer-grade to enterprise-level unmanned aerial systems (UASs) has resulted in the exponential use of these systems in many applications. Structure from motion with multiview stereo (SfM-MVS) photogrammetry is now the baseline for the development of orthoimages and 3D surfaces (e.g., digital elevation models). The horizontal and vertical positional accuracies (x, y and z) of these products in general, rely heavily on the use of ground control points (GCPs). However, for many applications, the use of GCPs is not possible. Here we tested 14 UASs to assess the positional and within-model accuracy of SfM-MVS reconstructions of low-relief landscapes without GCPs ranging from consumer to enterprise-grade vertical takeoff and landing (VTOL) platforms. We found that high positional accuracy is not necessarily related to the platform cost or grade, rather the most important aspect is the use of post-processing kinetic (PPK) or real-time kinetic (RTK) solutions for geotagging the photographs. SfM-MVS products generated from UAS with onboard geotagging, regardless of grade, results in greater positional accuracies and lower within-model errors. We conclude that where repeatability and adherence to a high level of accuracy are needed, only RTK and PPK systems should be used without GCPs.

scholarly journals Assessing the Accuracy of Digital Surface Models Derived from Optical Imagery Acquired with Unmanned Aerial Systems

Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 15 ◽  
Author(s):  
Salvatore Manfreda ◽  
Petr Dvorak ◽  
Jana Mullerova ◽  
Sorin Herban ◽  
Pietro Vuono ◽  
...  
Keyword(s):  
3D Model ◽  
Low Cost ◽  
Three Dimensional ◽  
Careful Consideration ◽  
Ground Control ◽  
Unmanned Aerial Systems ◽  
Control Points ◽  
Earthen Dam ◽  
Ground Control Points ◽  
Aerial Systems

Small unmanned aerial systems (UASs) equipped with an optical camera are a cost-effective strategy for topographic surveys. These low-cost UASs can provide useful information for three-dimensional (3D) reconstruction even if they are equipped with a low-quality navigation system. To ensure the production of high-quality topographic models, careful consideration of the flight mode and proper distribution of ground control points are required. To this end, a commercial UAS was adopted to monitor a small earthen dam using different combinations of flight configurations and by adopting a variable number of ground control points (GCPs). The results highlight that optimization of both the choice and combination of flight plans can reduce the relative error of the 3D model to within two meters without the need to include GCPs. However, the use of GCPs greatly improved the quality of the topographic survey, reducing error to the order of a few centimeters. The combined use of images extracted from two flights, one with a camera mounted at nadir and the second with a 20° angle, was found to be beneficial for increasing the overall accuracy of the 3D model and especially the vertical precision.

scholarly journals Measuring Height Characteristics of Sagebrush (Artemisia sp.) Using Imagery Derived from Small Unmanned Aerial Systems (sUAS)

Drones ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 6 ◽  
Author(s):  
Ryan G. Howell ◽  
Ryan R. Jensen ◽  
Steven L. Petersen ◽  
Randy T. Larsen
Keyword(s):  
Data Storage ◽  
Accuracy Assessment ◽  
Point Clouds ◽  
Unmanned Aerial Systems ◽  
Surface Model ◽  
Sage Grouse ◽  
Double Pass ◽  
Single Pass ◽  
3D Point Clouds ◽  
Aerial Systems

In situ measurements of sagebrush have traditionally been expensive and time consuming. Currently, improvements in small Unmanned Aerial Systems (sUAS) technology can be used to quantify sagebrush morphology and community structure with high resolution imagery on western rangelands, especially in sensitive habitat of the Greater sage-grouse (Centrocercus urophasianus). The emergence of photogrammetry algorithms to generate 3D point clouds from true color imagery can potentially increase the efficiency and accuracy of measuring shrub height in sage-grouse habitat. Our objective was to determine optimal parameters for measuring sagebrush height including flight altitude, single- vs. double- pass, and continuous vs. pause features. We acquired imagery using a DJI Mavic Pro 2 multi-rotor Unmanned Aerial Vehicle (UAV) equipped with an RGB camera, flown at 30.5, 45, 75, and 120 m and implementing single-pass and double-pass methods, using continuous flight and paused flight for each photo method. We generated a Digital Surface Model (DSM) from which we derived plant height, and then performed an accuracy assessment using on the ground measurements taken at the time of flight. We found high correlation between field measured heights and estimated heights, with a mean difference of approximately 10 cm (SE = 0.4 cm) and little variability in accuracy between flights with different heights and other parameters after statistical correction using linear regression. We conclude that higher altitude flights using a single-pass method are optimal to measure sagebrush height due to lower requirements in data storage and processing time.

scholarly journals Application of Miniaturized Sensors to Unmanned Aerial Systems, A New Pathway for the Survey of Polluted Areas: Preliminary Results

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 471 ◽  
Author(s):  
Francesca Fumian ◽  
Daniele Di Giovanni ◽  
Luca Martellucci ◽  
Riccardo Rossi ◽  
Pasqualino Gaudio
Keyword(s):  
Field Experiments ◽  
Risk Mitigation ◽  
Low Cost ◽  
Integrated System ◽  
Unmanned Aerial Systems ◽  
Preliminary Results ◽  
Standoff Detection ◽  
Set Up ◽  
Definition Of ◽  
Aerial Systems

With the aim to have risk mitigation for people and first responders, active remote sensing standoff detection is a fruitful technology, both in case of accidental (natural or incidental) or intentional dispersion in the environment of volatile chemical substances. Nowadays, several laser-based methodologies could be put in place to perform extensive areal monitoring. The present study regards the proposal for a new system architecture derived from the integration of a low-cost laser-based network of detectors for pollutants interfaced with a more sophisticated layout mounted on an unmanned aerial vehicle (UAV) able to identify the nature and the amount of a release. With this system set up, the drone will be activated by the alarm triggered by the laser-based network when anomalies are detected. The area will be explored by the drone with a more accurate set of sensors for identification to validate the detection of the network of Lidar systems and to sample the substance in the focus zone for subsequent analysis. In this work, methodologies and requirements for the standoff detection and the identification features chosen for this integrated system are described. The work aims at the definition of a new approach to the problem through the integration of different technologies and tools in the operative field experiments. Some preliminary results in support of the suitability of the integration hypothesis proposed are presented. This study gives rise to an integrated system to be furtherly tested in a real environment.

scholarly journals Assessing the Ability of Image Based Point Clouds Captured from a UAV to Measure the Terrain in the Presence of Canopy Cover

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 284 ◽  
Author(s):  
Luke Wallace ◽  
Chris Bellman ◽  
Bryan Hally ◽  
Jaime Hernandez ◽  
Simon Jones ◽  
...  
Keyword(s):  
Ground Surface ◽  
Canopy Cover ◽  
Weather Conditions ◽  
Point Clouds ◽  
Unmanned Aerial Systems ◽  
Image Capture ◽  
Terrain Model ◽  
Processing Strategies ◽  
Aerial Systems

Point clouds captured from Unmanned Aerial Systems are increasingly relied upon to provide information describing the structure of forests. The quality of the information derived from these point clouds is dependent on a range of variables, including the type and structure of the forest, weather conditions and flying parameters. A key requirement to achieve accurate estimates of height based metrics describing forest structure is a source of ground information. This study explores the availability and reliability of ground surface points available within point clouds captured in six forests of different structure (canopy cover and height), using three image capture and processing strategies, consisting of nadir, oblique and composite nadir/oblique image networks. The ground information was extracted through manual segmentation of the point clouds as well as through the use of two commonly used ground filters, LAStools lasground and the Cloth Simulation Filter. The outcomes of these strategies were assessed against ground control captured with a Total Station. Results indicate that a small increase in the number of ground points captured (between 0 and 5% of a 10 m radius plot) can be achieved through the use of a composite image network. In the case of manually identified ground points, this reduced the root mean square error (RMSE) error of the terrain model by between 1 and 11 cm, with greater reductions seen in plots with high canopy cover. The ground filters trialled were not able to exploit the extra information in the point clouds and inconsistent results in terrain RMSE were obtained across the various plots and imaging network configurations. The use of a composite network also provided greater penetration into the canopy, which is likely to improve the representation of mid-canopy elements.

Application of Postprocessing Kinematic Methods with UAS Remote Sensing in Forest Ecosystems

2021 ◽  
Author(s):  
Zachary M Miller ◽  
Joseph Hupy ◽  
Aishwarya Chandrasekaran ◽  
Guofan Shao ◽  
Songlin Fei
Keyword(s):  
Remote Sensing ◽  
Data Collection ◽  
Ground Control ◽  
Unmanned Aerial Systems ◽  
Control Points ◽  
Gps Technology ◽  
Ground Control Points ◽  
Forested Areas ◽  
Rapid Deployment ◽  
Aerial Systems

Abstract Unmanned Aerial Systems (UAS) serve as an excellent remote-sensing platform to fulfill an aerial imagery data collection niche previously unattainable in forestry by satellites and manned aircraft. However, for UAS-derived data to be spatially representative, a precise network of ground control points (GCP) is often required, which can be tedious and limit the logistical benefits of UAS rapid deployment capabilities, especially in densely forested areas. Therefore, methods for efficient data collection without GCPs are highly desired in UAS remote sensing. Here, we demonstrate the use of postprocessing kinematic (PPK) technology to obtain subcentimeter precision in datasets of forested areas without the need for placing GCPs. We evaluated two key measures, positional variability and time efficiency, of the PPK technology by comparing them to traditional GCP methods. Results show that PPK displays consistently higher positional precision than traditional GCP approaches. Moreover, PPK surveys and processing take less time to complete than traditional GCP methods and require fewer logistical steps, especially in image acquisition. The time and resource savings with PPK as compared to GCP processing are undeniable. We conclude that PPK technology provides a practical means to produce precise aerial forest surveys. Study Implications Unmanned Aerial Systems (UAS) have enormous potential for lowering costs and streamlining practices in the forestry management and research community. Despite this potential, however, UAS forestry applications have been limited in scope and precision because of a reliance on using ground-based GPS technology to survey ground control points (GCP), which are time intensive and require an open view of the sky. Such a need for a ground-based GCP survey, along with forest canopy serving to limit and scatter incoming GPS signals, diminishes the potential for rapid deployment and precision mapping offered by UAS. Fortunately, Postprocessing-Kinematic (PPK) GPS technology lowers these barriers by providing the means to seamlessly gather highly precise UAS imagery without needing to conduct time-intensive ground-based surveys. This study compares the precision and time-effectiveness between traditional GCP marker surveys and PPK correction methods.

scholarly journals Evaluation of Ground Surface Models Derived from Unmanned Aerial Systems with Digital Aerial Photogrammetry in a Disturbed Conifer Forest

2019 ◽  
Vol 11 (1) ◽  
pp. 84 ◽  
Author(s):  
Alexander Graham ◽  
Nicholas Coops ◽  
Michael Wilcox ◽  
Andrew Plowright
Keyword(s):  
Canopy Cover ◽  
Point Clouds ◽  
Unmanned Aerial Systems ◽  
Optimal Parameters ◽  
Conifer Forest ◽  
Terrain Modeling ◽  
Ground Truth Data ◽  
Aerial Photogrammetry ◽  
Terrain Slope ◽  
Aerial Systems

Detailed vertical forest structure information can be remotely sensed by combining technologies of unmanned aerial systems (UAS) and digital aerial photogrammetry (DAP). A key limitation in the application of DAP methods, however, is the inability to produce accurate digital elevation models (DEM) in areas of dense vegetation. This study investigates the terrain modeling potential of UAS-DAP methods within a temperate conifer forest in British Columbia, Canada. UAS-acquired images were photogrammetrically processed to produce high-resolution DAP point clouds. To evaluate the terrain modeling ability of DAP, first, a sensitivity analysis was conducted to estimate optimal parameters of three ground-point classification algorithms designed for airborne laser scanning (ALS). Algorithms tested include progressive triangulated irregular network (TIN) densification (PTD), hierarchical robust interpolation (HRI) and simple progressive morphological filtering (SMRF). Points were classified as ground from the ALS and served as ground-truth data to which UAS-DAP derived DEMs were compared. The proportion of area with root mean square error (RMSE) <1.5 m were 56.5%, 51.6% and 52.3% for the PTD, HRI and SMRF methods respectively. To assess the influence of terrain slope and canopy cover, error values of DAP-DEMs produced using optimal parameters were compared to stratified classes of canopy cover and slope generated from ALS point clouds. Results indicate that canopy cover was approximately three times more influential on RMSE than terrain slope.

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