scholarly journals UAV VISUAL AUTOLOCALIZATON BASED ON AUTOMATIC LANDMARK RECOGNITION

2017 ◽  
Vol IV-2/W3 ◽  
pp. 89-94 ◽  
Author(s):  
P. Silva Filho ◽  
E. H. Shiguemori ◽  
O. Saotome
Keyword(s):  
Computer Vision ◽  
Scientific Community ◽  
Aerial Images ◽  
Gps Data ◽  
Navigation Systems ◽  
Landmark Recognition ◽  
Simulated Environment ◽  
Vision Based Navigation ◽  
Aerial Vehicle ◽  
Uav Navigation

Deploying an autonomous unmanned aerial vehicle in GPS-denied areas is a highly discussed problem in the scientific community. There are several approaches being developed, but the main strategies yet considered are computer vision based navigation systems. This work presents a new real-time computer-vision position estimator for UAV navigation. The estimator uses images captured during flight to recognize specific, well-known, landmarks in order to estimate the latitude and longitude of the aircraft. The method was tested in a simulated environment, using a dataset of real aerial images obtained in previous flights, with synchronized images, GPS and IMU data. The estimated position in each landmark recognition was compatible with the GPS data, stating that the developed method can be used as an alternative navigation system.

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

scholarly journals Pose Measurement for Unmanned Aerial Vehicle Based on Rigid Skeleton

2021 ◽  
Vol 11 (4) ◽  
pp. 1373
Author(s):  
Jingyu Zhang ◽  
Zhen Liu ◽  
Guangjun Zhang
Keyword(s):  
Measurement Errors ◽  
Structural Characteristics ◽  
Geometric Model ◽  
Formation Flight ◽  
Depth Information ◽  
Feature Points ◽  
Feature Point Extraction ◽  
Aerial Vehicle ◽  
Uav Navigation ◽  
Rigid Skeleton

Pose measurement is a necessary technology for UAV navigation. Accurate pose measurement is the most important guarantee for a UAV stable flight. UAV pose measurement methods mostly use image matching with aircraft models or 2D points corresponding with 3D points. These methods will lead to pose measurement errors due to inaccurate contour and key feature point extraction. In order to solve these problems, a pose measurement method based on the structural characteristics of aircraft rigid skeleton is proposed in this paper. The depth information is introduced to guide and label the 2D feature points to eliminate the feature mismatch and segment the region. The space points obtained from the marked feature points fit the space linear equation of the rigid skeleton, and the UAV attitude is calculated by combining with the geometric model. This method does not need cooperative identification of the aircraft model, and can stably measure the position and attitude of short-range UAV in various environments. The effectiveness and reliability of the proposed method are verified by experiments on a visual simulation platform. The method proposed can prevent aircraft collision and ensure the safety of UAV navigation in autonomous refueling or formation flight.

Subglacial topography and thickness of ice caps on the Argentine Islands

2019 ◽  
Vol 31 (6) ◽  
pp. 332-344 ◽  
Author(s):  
Jānis Karušs ◽  
Kristaps Lamsters ◽  
Anatolii Chernov ◽  
Māris Krievāns ◽  
Jurijs Ješkins
Keyword(s):  
Land Surface ◽  
Geological Structure ◽  
Aerial Images ◽  
Ice Thickness ◽  
Ice Caps ◽  
The North ◽  
Prevailing Wind Direction ◽  
Aerial Vehicle ◽  
Subglacial Topography ◽  
Ground Penetrating

AbstractThis study presents the first subglacial topography and ice thickness models of the largest ice caps of the Argentine Islands, Wilhelm Archipelago, West Antarctica. During this study, ground-penetrating radar was used to map the thickness and inner structure of the ice caps. Digital surface models of all studied islands were created from aerial images obtained with a small-sized unmanned aerial vehicle and used for the construction of subglacial topography models. Ice caps of the Argentine Islands cover ~50% of the land surface of the islands on average. The maximum thickness of only two islands (Galindez and Skua) exceeds 30 m, while the average thickness of all islands is only ~5 m. The maximum ice thickness reaches 35.3 m on Galindez Island. The ice thickness and glacier distribution are mainly governed by prevailing wind direction from the north. This has created the prominent narrow ice ridges on Uruguay and Irizar islands, which are not supported by topographic obstacles, as well as the elongated shape of other ice caps. The subglacial topography of the ice caps is undulated and mainly dependent on the geological structure and composition of magmatic rocks.

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.

Autonomous Unmanned Aerial Vehicle for Post-Disaster Management With Cognitive Radio Communication

2021 ◽  
Vol 12 (1) ◽  
pp. 29-52
Author(s):  
Raja Guru R. ◽  
Naresh Kumar P.
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Processing Technique ◽  
High Accuracy ◽  
Image Processing Technique ◽  
Radio Communication ◽  
Dynamic Changes ◽  
General Graph ◽  
Vision Based Navigation ◽  
Aerial Vehicle ◽  
Post Disaster

Unmanned aerial vehicles (UAV) play a significant role in finding victims affected in the post-disaster zone, where a man cannot risk his life under a critical condition of the disaster environment. The proposed design incorporates autonomous vision-based navigation through the disaster environment based on general graph theory with dynamic changes on the length between two or multiple nodes, where a node is a pathway. Camera fixed on it continuously captures the surrounding footage, processing it frame by frame on-site using image processing technique based on a SOC. Identifies victims in the zone and the pathways available for traversal. UAV uses an ultrasonic rangefinder to avoid collision with obstacles. The system alerts the rescue team if any victim detected and transmits the frames using CRN to the off-site console. UAV learns navigation policy that achieves high accuracy in real-time environments; communication using CRN is uninterrupted and useful during such emergencies.

Multi-UAV Specification and Control with a Single Pilot-in-the-Loop

2020 ◽  
Vol 08 (04) ◽  
pp. 269-277
Author(s):  
Patricio Moreno ◽  
Santiago Esteva ◽  
Ignacio Mas ◽  
Juan I. Giribet
Keyword(s):  
Remote Control ◽  
Unmanned Aerial Vehicles ◽  
Field Experiments ◽  
Aerial Vehicles ◽  
Simulated Environment ◽  
Aerial Vehicle ◽  
Space Formulation ◽  
Trajectory Following ◽  
And Control ◽  
Multi Uav

This work presents a multi-unmanned aerial vehicle formation implementing a trajectory-following controller based on the cluster-space robot coordination method. The controller is augmented with a feed-forward input from a control station operator. This teleoperation input is generated by means of a remote control, as a simple way of modifying the trajectory or taking over control of the formation during flight. The cluster-space formulation presents a simple specification of the system’s motion and, in this work, the operator benefits from this capability to easily evade obstacles by means of controlling the cluster parameters in real time. The proposed augmented controller is tested in a simulated environment first, and then deployed for outdoor field experiments. Results are shown in different scenarios using a cluster of three autonomous unmanned aerial vehicles.

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