scholarly journals Practical Aspects of Design and Testing Unmanned Aerial Vehicles

2020 ◽  
Vol 14 (1) ◽  
pp. 50-58
Author(s):  
Patryk Szywalski ◽  
Andrzej Waindok
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Global Positioning System ◽  
Practical Implementation ◽  
Positioning System ◽  
Positioning Systems ◽  
Autonomous Flight ◽  
Aerial Vehicles ◽  
Global Positioning ◽  
Aerial Vehicle ◽  
Design And Testing

AbstractA design of an unmanned aerial vehicle (UAV) construction, intended for autonomous flights in a group, was presented in this article. The design assumptions, practical implementation and results of the experiments were given. Some of the frame parts were made using 3D printing technology. It not only reduces the costs but also allows for better fitting of the covers to the electronics, which additionally protects them against shocks and dirt. The most difficult task was to develop the proper navigation system. Owing to high costs of precision positioning systems, common global positioning system (GPS) receivers were used. Their disadvantage is the floating position error. The original software was also described. It controls the device, allows performing autonomous flight along a pre-determined route, analyses all parameters of the drone and sends them in a real time to the operator. The tests of the system were carried out and presented in the article, as well.

scholarly journals POTENTIAL OF UNMANNED AERIAL VEHICLES FOR AGRICULTURE

2021 ◽  
Vol 3 (1) ◽  
pp. 1-8
Author(s):  
Pawan Thapa
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Real Time ◽  
Global Positioning System ◽  
Crop Production ◽  
Positioning System ◽  
Interactive Maps ◽  
Aerial Vehicles ◽  
Global Positioning ◽  
Farmer Management ◽  
User Friendly

In few years, agriculture drones emerge for monitoring, planting, spraying, and mapping to increase crop production and reduce labor. This review results show its significance and farmer's demand for agriculture. The UAV technologies enable farmer management based on measuring and observation based on real-time crop and livestock monitoring, significantly maximize their production. The farm drone consists of user-friendly software with interactive maps, and a global positioning system will improve production. It will support farmer for farming in efficient, effective, and economical ways.

A Visual Global Positioning System for Unmanned Aerial Vehicles Used in Photogrammetric Applications

2010 ◽  
Vol 61 (1-4) ◽  
pp. 157-168 ◽  
Author(s):  
Andrea Cesetti ◽  
Emanuele Frontoni ◽  
Adriano Mancini ◽  
Andrea Ascani ◽  
Primo Zingaretti ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Global Positioning System ◽  
Positioning System ◽  
Aerial Vehicles ◽  
Global Positioning

A Visual Global Positioning System for Unmanned Aerial Vehicles Used in Photogrammetric Applications

2010 ◽  
pp. 157-168
Author(s):  
Andrea Cesetti ◽  
Emanuele Frontoni ◽  
Adriano Mancini ◽  
Andrea Ascani ◽  
Primo Zingaretti ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Global Positioning System ◽  
Positioning System ◽  
Aerial Vehicles ◽  
Global Positioning

scholarly journals Dynamic Selection Techniques for Detecting GPS Spoofing Attacks on UAVs

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 662
Author(s):  
Tala Talaei Khoei ◽  
Shereen Ismail ◽  
Naima Kaabouch
Keyword(s):  
False Alarm ◽  
Unmanned Aerial Vehicles ◽  
Global Positioning System ◽  
Processing Time ◽  
Probability Of Detection ◽  
Positioning System ◽  
Dynamic Selection ◽  
Probability Of False Alarm ◽  
Aerial Vehicles ◽  
Global Positioning

Unmanned aerial vehicles are prone to several cyber-attacks, including Global Positioning System spoofing. Several techniques have been proposed for detecting such attacks. However, the recurrence and frequent Global Positioning System spoofing incidents show a need for effective security solutions to protect unmanned aerial vehicles. In this paper, we propose two dynamic selection techniques, Metric Optimized Dynamic selector and Weighted Metric Optimized Dynamic selector, which identify the most effective classifier for the detection of such attacks. We develop a one-stage ensemble feature selection method to identify and discard the correlated and low importance features from the dataset. We implement the proposed techniques using ten machine-learning models and compare their performance in terms of four evaluation metrics: accuracy, probability of detection, probability of false alarm, probability of misdetection, and processing time. The proposed techniques dynamically choose the classifier with the best results for detecting attacks. The results indicate that the proposed dynamic techniques outperform the existing ensemble models with an accuracy of 99.6%, a probability of detection of 98.9%, a probability of false alarm of 1.56%, a probability of misdetection of 1.09%, and a processing time of 1.24 s.

Ultra-Wideband-Based Localization for Quadcopter Navigation

2016 ◽  
Vol 04 (01) ◽  
pp. 23-34 ◽  
Author(s):  
Kexin Guo ◽  
Zhirong Qiu ◽  
Cunxiao Miao ◽  
Abdul Hanif Zaini ◽  
Chun-Lin Chen ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Global Positioning System ◽  
Ultra Wideband ◽  
Line Of Sight ◽  
Positioning System ◽  
Localization Algorithm ◽  
Control Loop ◽  
Flight Tests ◽  
Localization System ◽  
Global Positioning

Micro unmanned aerial vehicles (UAVs) are promising to play more and more important roles in both civilian and military activities. Currently, the navigation of UAVs is critically dependent on the localization service provided by the Global Positioning System (GPS), which suffers from the multipath effect and blockage of line-of-sight, and fails to work in an indoor, forest or urban environment. In this paper, we establish a localization system for quadcopters based on ultra-wideband (UWB) range measurements. To achieve the localization, a UWB module is installed on the quadcopter to actively send ranging requests to some fixed UWB modules at known positions (anchors). Once a distance is obtained, it is calibrated first and then goes through outlier detection before being fed to a localization algorithm. The localization algorithm is initialized by trilateration and sustained by the extended Kalman filter (EKF). The position and velocity estimates produced by the algorithm will be further fed to the control loop to aid the navigation of the quadcopter. Various flight tests in different environments have been conducted to validate the performance of UWB ranging and localization algorithm.

scholarly journals A low-cost solution for unmanned aerial vehicle navigation in a global positioning system–denied environment

2018 ◽  
Vol 14 (6) ◽  
pp. 155014771878175 ◽  
Author(s):  
Shahrukh Ashraf ◽  
Priyanka Aggarwal ◽  
Praveen Damacharla ◽  
Hong Wang ◽  
Ahmad Y Javaid ◽  
...  
Keyword(s):  
Optical Flow ◽  
Unmanned Aerial Vehicle ◽  
Global Positioning System ◽  
Motion Vector ◽  
Block Matching ◽  
Positioning System ◽  
Simulation Studies ◽  
Flow Measurements ◽  
Global Positioning ◽  
Aerial Vehicle

The ability of an autonomous unmanned aerial vehicle to navigate and fly precisely determines its utility and performance. The current navigation systems are highly dependent on the global positioning system and are prone to error because of global positioning system signal outages. However, advancements in onboard processing have enabled inertial navigation algorithms to perform well during short global positioning system outages. In this article, we propose an intelligent optical flow–based algorithm combined with Kalman filters to provide the navigation capability during global positioning system outages and global positioning system–denied environments. Traditional optical flow measurement uses block matching for motion vector calculation that makes the measurement task computationally expensive and slow. We propose the application of an artificial bee colony–based block matching technique for faster optical flow measurements. To effectively fuse optical flow data with inertial sensors output, we employ a modified form of extended Kalman filter. The modifications make the filter less noisy by utilizing the redundancy of sensors. We have achieved an accuracy of ~95% for all non-global positioning system navigation during our simulation studies. Our real-world experiments are in agreement with the simulation studies when effects of wind are taken into consideration.

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