scholarly journals Developing a Modular Unmanned Aerial Vehicle (UAV) Platform for Air Pollution Profiling

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4363 ◽  
Author(s):  
Qijun Gu ◽  
Drew R. Michanowicz ◽  
Chunrong Jia
Keyword(s):  
Air Quality ◽  
Data Fusion ◽  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
High Precision ◽  
Flight Control ◽  
Quality Data ◽  
Sample Collection ◽  
Ground Station ◽  
Aerial Vehicle

The unmanned aerial vehicle (UAV) offers great potential for collecting air quality data with high spatial and temporal resolutions. The objective of this study is to design and develop a modular UAV-based platform capable of real-time monitoring of multiple air pollutants. The system comprises five modules: the UAV, the ground station, the sensors, the data acquisition (DA) module, and the data fusion (DF) module. The hardware was constructed with off-the-shelf consumer parts and the open source software Ardupilot was used for flight control and data fusion. The prototype UAV system was tested in representative settings. Results show that this UAV platform can fly on pre-determined pathways with adequate flight time for various data collection missions. The system simultaneously collects air quality and high precision X-Y-Z data and integrates and visualizes them in a real-time manner. While the system can accommodate multiple gas sensors, UAV operations may electronically interfere with the performance of chemical-resistant sensors. Our prototype and experiments prove the feasibility of the system and show that it features a stable and high precision spatial-temporal platform for air sample collection. Future work should be focused on gas sensor development, plug-and-play interfaces, impacts of rotor wash, and all-weather designs.

scholarly journals Real-Time Onboard 3D State Estimation of an Unmanned Aerial Vehicle in Multi-Environments Using Multi-Sensor Data Fusion

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 919 ◽  
Author(s):  
Hao Du ◽  
Wei Wang ◽  
Chaowen Xu ◽  
Ran Xiao ◽  
Changyin Sun
Keyword(s):  
Data Fusion ◽  
State Estimation ◽  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
Position Estimation ◽  
Sensor Data ◽  
Measurement Unit ◽  
Sensor Data Fusion ◽  
Multi Sensor Data Fusion ◽  
Aerial Vehicle

The question of how to estimate the state of an unmanned aerial vehicle (UAV) in real time in multi-environments remains a challenge. Although the global navigation satellite system (GNSS) has been widely applied, drones cannot perform position estimation when a GNSS signal is not available or the GNSS is disturbed. In this paper, the problem of state estimation in multi-environments is solved by employing an Extended Kalman Filter (EKF) algorithm to fuse the data from multiple heterogeneous sensors (MHS), including an inertial measurement unit (IMU), a magnetometer, a barometer, a GNSS receiver, an optical flow sensor (OFS), Light Detection and Ranging (LiDAR), and an RGB-D camera. Finally, the robustness and effectiveness of the multi-sensor data fusion system based on the EKF algorithm are verified by field flights in unstructured, indoor, outdoor, and indoor and outdoor transition scenarios.

Development of the navigation complex structure for a high-precision unmanned aerial vehicle for flight in the atmosphere

2020 ◽  
Keyword(s):  
Mathematical Modeling ◽  
Unmanned Aerial Vehicle ◽  
High Precision ◽  
Kalman Filters ◽  
Inertial Navigation System ◽  
Complex Structure ◽  
Navigation Systems ◽  
Aerial Vehicle ◽  
Low Altitude ◽  
System Errors

The navigation systems as part of the navigation complex of a high-precision unmanned aerial vehicle in conditions of different altitude flight are investigated. The working contours of the navigation complex with correction algorithms for an unmanned aerial vehicle during high-altitude and low-altitude flights are formed. Mathematical models of inertial navigation system errors used in non-linear and linear Kalman filters are presented. The results of mathematical modeling demonstrate the effectiveness of the working contours effectiveness of the navigation complex with correction algorithms. Keywords high-precision unmanned aerial vehicle; navigation complex; multi-altitude flight; work circuit; passive noises; Kalman filter; correction

Joint Mechanical Design and Flight Control Optimization of a Nature-Inspired Unmanned Aerial Vehicle via Collaborative Co-Evolution

2021 ◽  
Vol 6 (2) ◽  
pp. 2044-2051
Author(s):  
Danial Sufiyan ◽  
Luke Soe Thura Win ◽  
Shane Kyi Hla Win ◽  
Gim Song Soh ◽  
Shaohui Foong
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Flight Control ◽  
Mechanical Design ◽  
Control Optimization ◽  
Aerial Vehicle

scholarly journals Improvement in energy conversion for unmanned aerial vehicle charging pad

2020 ◽  
Vol 17 (2) ◽  
pp. 767
Author(s):  
M. R. AL-Obaidi ◽  
M. A. Mustafa ◽  
W.Z.W. Hassan ◽  
N. Azis ◽  
A. H. Sabry ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Design Methodology ◽  
Font Size ◽  
Contact Charging ◽  
Charging Station ◽  
Ground Station ◽  
Landing Platform ◽  
Aerial Vehicle ◽  
Fully Automatic ◽  
Software And Hardware

<span style="font-size: 9pt; font-family: 'Times New Roman', serif;">An efficient charging station is a necessity for Unmanned Aerial Vehicle (UAV) systems. However, if that implementation adds more complexity and onboard weight, then that exercise becomes a burden rather than a benefit since UAV's engineers aim to improve efficiency by reducing the energy consumed by the software and hardware of the complete aeronautical system. This article recommends a fully automatic contact charging station for UAVs, which can charge UAVs and thus resolve flight endurance restrictions of the UAV. The ground station consists of square copper plates that are positively and negatively polarized successively in a chessboard with particular sizes to guarantee electric contact at the landing. The design methodology used with the loading station takes into account the differences in UAV orientation once the platform has landed. In addition, this innovation uses independent charging after touchdown. Thus, this technology relaxes common flight times and help to enhance general mission times. This paper presents a unique charging platform in a “chessboard” configuration, which is devised as an interconnecting interface to facilitate the charging process and overcome inaccuracies with the landing. The solution devised in this research requires few components and presents two power source options (solar &amp; mains power). Additionally, this work presents, to the best of our knowledge, a uniquely innovative recharging landing platform, which incidentally requires no additional software or changes to the UAV’s onboard software settings</span><span style="font-size: 9pt; font-family: Arial, sans-serif;">.</span>

scholarly journals Pemanfaatan Metode Fotogrametri untuk Pengukuran Garis Pantai dan Identifikasi Objek-Objek Tematik dengan Menggunakan Wahana Uav (Unmanned Aerial Vehicle) (Studi Kasus Pengukuran Garis Pantai di Pangkalan TNI AL Pondok Dayung

2020 ◽  
Vol 5 (1) ◽  
pp. 71-84
Author(s):  
Adhyta Harfan ◽  
Dipo Yudhatama ◽  
Imam Bachrodin
Keyword(s):  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
Control Point ◽  
Ground Control ◽  
Ground Control Point ◽  
Real Time Kinematic ◽  
Aerial Vehicle

Metode Fotogrametri telah banyak digunakan dalam survei dan pemetaan. Seiring dengan kemajuan ilmu pengetahuan dan teknologi, metode fotogrametri saat ini berbasiskan pesawat tanpa awak atau yang lebih dikenal dengan UAV (Unmanned Aerial Vehicle). Kelebihan metode fotogrametri berbasiskan UAV untuk pengukuran garis pantai adalah memiliki resolusi spasial yang sangat tinggi dan dapat menjagkau daerah-daerah yang sulit dan berbahaya. Di samping itu juga dapat memberikan data foto udara terkini dengan sekala detail. Dalam penelitian ini membandingkan ketelitian horisontal antara hasil pengukuran garis pantai menggunakan metode fotogrametri berbasiskan UAV secara rektifikasi dengan GCP (Ground Control Point) maupun secara PPK (Post Processed Kinematic) dengan pengukuran garis pantai metode GNSS RTK (Real Time Kinematic). Hasil perhitungan ketelitian horisontal mengacu pada standar publikasi IHO S-44 tentang pengukuran garis pantai. Pemotretan dilakukan dengan ketinggian terbang 180 m, dengan tampalan depan dan samping 80%. Hasil perhitungan ketelitian horisontal foto udara terektifikasi 5 GCP, foto udara PPK dan foto udara PPK terektifikasi 1 GCP terhadap pengukuran garis pantai dengan metode GNSS RTK diperoleh nilai standar deviasi (σ) dan 95% selang kepercayaan (CI95%) masing-masing sebagai berikut: σ5gcp=10,989 cm dengan CI95% 16.8 cm < μ < 21.2 cm , σppk=26,066 cm dengan CI95% 26.5 cm < μ < 37 cm dan σppk1gcp=10,378 cm dengan CI95% 15.6 cm < μ < 19.8 cm. Kemudian terdapat 10 objek tematik berdasarkan Peta Laut Nomor 1 yang dapat diinterpretasi pada hasil orthomosaic foto udara.

scholarly journals Utilizing drone technology in the civil engineering

2019 ◽  
Vol 14 (1) ◽  
pp. 27-37
Author(s):  
Matúš Tkáč ◽  
Peter Mésároš
Keyword(s):  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
Civil Engineering ◽  
Aerial Images ◽  
General Overview ◽  
Aerial Photogrammetry ◽  
Different Types ◽  
Aerial Vehicle

Abstract An unmanned aerial vehicle (UAVs), also known as drone technology, is used for different types of application in the civil engineering. Drones as a tools that increase communication between construction participants, improves site safety, uses topographic measurements of large areas, with using principles of aerial photogrammetry is possible to create buildings aerial surveying, bridges, roads, highways, saves project time and costs, etc. The use of UAVs in the civil engineering can brings many benefits; creating real-time aerial images from the building objects, overviews reveal assets and challenges, as well as the broad lay of the land, operators can share the imaging with personnel on site, in headquarters and with sub-contractors, planners can meet virtually to discuss project timing, equipment needs and challenges presented by the terrain. The aim of this contribution is to create a general overview of the use of UAVs in the civil engineering. The contribution also contains types of UAVs used for construction purposes, their advantages and also disadvantages.

scholarly journals Wheat Leaf Area Index Prediction Using Data Fusion Based on High-Resolution Unmanned Aerial Vehicle Imagery

2021 ◽  
Author(s):  
Shuang Wu ◽  
Lei Deng ◽  
Lijie Guo ◽  
Yanjie Wu
Keyword(s):  
High Resolution ◽  
Data Fusion ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Unmanned Aerial Vehicle ◽  
Prediction Accuracy ◽  
Sensor Data ◽  
Support Vector ◽  
Area Index ◽  
Aerial Vehicle

Abstract Background: Leaf Area Index (LAI) is half of the amount of leaf area per unit horizontal ground surface area. Consequently, accurate vegetation extraction in remote sensing imagery is critical for LAI estimation. However, most studies do not fully exploit the advantages of Unmanned Aerial Vehicle (UAV) imagery with high spatial resolution, such as not removing the background (soil and shadow, etc.). Furthermore, the advancement of multi-sensor synchronous observation and integration technology allows for the simultaneous collection of canopy spectral, structural, and thermal data, making it possible for data fusion.Methods: To investigate the potential of high-resolution UAV imagery combined with multi-sensor data fusion in LAI estimation. High-resolution UAV imagery was obtained with a multi-sensor integrated MicaSense Altum camera to extract the wheat canopy's spectral, structural, and thermal features. After removing the soil background, all features were fused, and LAI was estimated using Random Forest and Support Vector Machine Regression.Result: The results show that: (1) the soil background reduced the accuracy of the LAI prediction, and soil background could be effectively removed by taking advantage of high-resolution UAV imagery. After removing the soil background, the LAI prediction accuracy improved significantly, R2 raised by about 0.27, and RMSE fell by about 0.476. (2) The fusion of multi-sensor synchronous observation data improved LAI prediction accuracy and achieved the best accuracy (R2 = 0.815 and RMSE = 1.023). (3) When compared to other variables, 23 CHM, NRCT, NDRE, and BLUE are crucial for LAI estimation. Even the simple Multiple Linear Regression model could achieve high prediction accuracy (R2 = 0.679 and RMSE = 1.231), providing inspiration for rapid and efficient LAI prediction.Conclusions: The method of this study can be transferred to other sites with more extensive areas or similar agriculture structures, which will facilitate agricultural production and management.

scholarly journals 1A2-O11 Development and Flight Control of an Unmanned Aerial Vehicle That Has a Vertical Canard(Aerial Robot and Mechatronics)

2011 ◽  
Vol 2011 (0) ◽  
pp. _1A2-O11_1-_1A2-O11_4
Author(s):  
Kenta Go ◽  
Atsushi KONNO ◽  
Takaaki MATSUMOTO ◽  
Atsushi OOSEDO ◽  
Kouji MASUKO ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Flight Control ◽  
Aerial Robot ◽  
Aerial Vehicle
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