scholarly journals Feasibility study of using the RoboEarth cloud engine for rapid mapping and tracking with small unmanned aerial systems

2014 ◽  
Vol XL-1 ◽  
pp. 219-226 ◽  
Author(s):  
J. Li-Chee-Ming ◽  
C. Armenakis
Keyword(s):  
Data Storage ◽  
Large Data ◽  
Video Camera ◽  
Sensor Data ◽  
Single Frequency ◽  
Unmanned Aerial Systems ◽  
Indoor Environments ◽  
Processing Strategies ◽  
Outdoor Environments ◽  
Aerial Systems

This paper presents the ongoing development of a small unmanned aerial mapping system (sUAMS) that in the future will track its trajectory and perform 3D mapping in near-real time. As both mapping and tracking algorithms require powerful computational capabilities and large data storage facilities, we propose to use the RoboEarth Cloud Engine (RCE) to offload heavy computation and store data to secure computing environments in the cloud. While the RCE's capabilities have been demonstrated with terrestrial robots in indoor environments, this paper explores the feasibility of using the RCE in mapping and tracking applications in outdoor environments by small UAMS. <br><br> The experiments presented in this work assess the data processing strategies and evaluate the attainable tracking and mapping accuracies using the data obtained by the sUAMS. Testing was performed with an Aeryon Scout quadcopter. It flew over York University, up to approximately 40 metres above the ground. The quadcopter was equipped with a single-frequency GPS receiver providing positioning to about 3 meter accuracies, an AHRS (Attitude and Heading Reference System) estimating the attitude to about 3 degrees, and an FPV (First Person Viewing) camera. Video images captured from the onboard camera were processed using VisualSFM and SURE, which are being reformed as an Application-as-a-Service via the RCE. The 3D virtual building model of York University was used as a known environment to georeference the point cloud generated from the sUAMS' sensor data. The estimated position and orientation parameters of the video camera show increases in accuracy when compared to the sUAMS' autopilot solution, derived from the onboard GPS and AHRS. The paper presents the proposed approach and the results, along with their accuracies.

Joint Chilean and US mobility testing in extreme environments

2021 ◽  
Author(s):  
Michael Parker ◽  
Alex Stott ◽  
Brian Quinn ◽  
Bruce Elder ◽  
Tate Meehan ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Extreme Environments ◽  
Sensor Data ◽  
Unmanned Aerial Systems ◽  
Area Network ◽  
The Us ◽  
Vehicle Mobility ◽  
Data Collections ◽  
Aerial Systems ◽  
Vehicle Sensor

Vehicle mobility in cold and challenging terrains is of interest to both the US and Chilean Armies. Mobility in winter conditions is highly vehicle dependent with autonomous vehicles experiencing additional challenges over manned vehicles. They lack the ability to make informed decisions based on what they are “seeing” and instead need to rely on input from sensors on the vehicle, or from Unmanned Aerial Systems (UAS) or satellite data collections. This work focuses on onboard vehicle Controller Area Network (CAN) Bus sensors, driver input sensors, and some externally mounted sensors to assist with terrain identification and overall vehicle mobility. Analysis of winter vehicle/sensor data collected in collaboration with the Chilean Army in Lonquimay, Chile during July and August 2019 will be discussed in this report.

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 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.

scholarly journals A FEASIBILITY STUDY ON USING ViSP’S 3D MODEL-BASED TRACKER FOR UAV POSE ESTIMATION IN OUTDOOR ENVIRONMENTS

2015 ◽  
Vol XL-1/W4 ◽  
pp. 329-335 ◽  
Author(s):  
J. Li-Chee-Ming ◽  
C. Armenakis
Keyword(s):  
Pose Estimation ◽  
Visual Servoing ◽  
3D Model ◽  
Initial Approximation ◽  
Indoor Environments ◽  
Processing Strategies ◽  
Building Models ◽  
Small Uav ◽  
Outdoor Environments ◽  
Camera Position

This paper presents a novel application of the Visual Servoing Platform’s (ViSP) for small UAV pose estimation in outdoor environments. Given an initial approximation for the camera position and orientation, or camera pose, ViSP automatically establishes and continuously tracks corresponding features between an image sequence and a 3D wireframe model of the environment. As ViSP has been demonstrated to perform well in small and cluttered indoor environments, this paper explores the application of ViSP for UAV mapping of outdoor landscapes and tracking of large objects (i.e. building models). Our presented experiments demonstrate the data obtainable by the UAV, assess ViSP’s data processing strategies, and evaluate the performance of the tracker.

scholarly journals HS-SA-Based Precise Modeling of the Aircraft Fuel Center of Gravity Using Sensors Data

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2457 ◽  
Author(s):  
Xiaoming Guo ◽  
Jing Zhang ◽  
Lin Tie ◽  
Mingqiang Luo
Keyword(s):  
Data Storage ◽  
Heuristic Search ◽  
Large Data ◽  
Center Of Gravity ◽  
Sensor Data ◽  
Nonlinear Characteristics ◽  
Modeling Methods ◽  
Aircraft Fuel ◽  
Multidimensional Interpolation ◽  
Temporal Efficiency

The traditional modeling methods of aircraft fuel center of gravity (CG) based on sensor data have some disadvantages, such as large data storage requirements and low computational efficiency. In this article, a novel hybrid heuristic search-simulated annealing (HS-SA) algorithm is used to reduce the data storage requirements and improve the efficiency of the established models based on sensor data. First, a fuel CG model is established based on the multidimensional interpolation of flight sensors and fuel tank data, which can accurately reflect the nonlinear characteristics of the problem and reduce the data storage needs. Then, the calculation nodes are reasonably selected and optimized based on the proposed HS-SA algorithm to improve the precision of the model of the aircraft fuel CG. The established model of the fuel CG has obvious advantages over traditional methods in improving the temporal efficiency and meeting the storage requirements for sensor data in actual flights. Finally, detailed simulations are conducted based on more than 16,000 sets of sensor data, and the results demonstrate the effectiveness of the proposed HS-SA algorithm.

LIGHTER-THAN-AIR (LTA) UNMANNED AERIAL SYSTEM (UAS) CARRIER CONCEPT FOR SURVAILLANCE AND DISASTER MANAGEMENT

2019 ◽  
Vol 3 ◽  
pp. 1255
Author(s):  
Ahmad Salahuddin Mohd Harithuddin ◽  
Mohd Fazri Sedan ◽  
Syaril Azrad Md Ali ◽  
Shattri Mansor ◽  
Hamid Reza Jifroudi ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Disaster Management ◽  
Unmanned Aerial Systems ◽  
Unmanned Aerial System ◽  
Border Control ◽  
Aerial Vehicles ◽  
Operational Safety ◽  
In Situ Methods ◽  
Aerial Systems

Unmanned aerial systems (UAS) has many advantages in the fields of SURVAILLANCE and disaster management compared to space-borne observation, manned missions and in situ methods. The reasons include cost effectiveness, operational safety, and mission efficiency. This has in turn underlined the importance of UAS technology and highlighted a growing need in a more robust and efficient unmanned aerial vehicles to serve specific needs in SURVAILLANCE and disaster management. This paper first gives an overview on the framework for SURVAILLANCE particularly in applications of border control and disaster management and lists several phases of SURVAILLANCE and service descriptions. Based on this overview and SURVAILLANCE phases descriptions, we show the areas and services in which UAS can have significant advantage over traditional methods.

Sign in / Sign up

Export Citation Format

Share Document