Orientation Of Unmanned Aerial Vehicle Research Articles

ERROR ANALYSIS OF VISUAL ODOMETRY FOR A SMALL SIZE UNMANNED AERIAL VEHICLE

Abstract. Usage of small size Unmanned Aerial Vehicle (UAV) with autonomous flight capability became widespread at both civil and military applications because of its low costs and ease of use. However, inertial or GPS based positioning and orientation sensors can be disabled at battlefields and the UAV losses its path in a short time. Visual odometry becomes a solution for the aforementioned hassle. Real-time detection of ground control points, matching the same control points at the stereo pair images and correcting the position and orientation data with least square adjustment are the challenges of visual odometry. In this study, error analysis of position and orientation of a UAV flying through mountainous region which cannot obtain any augmenting data for position and orientation is conducted by error propagation law. The flight of UAV is simulated with exact initial position and orientation data. Optic images of ground obtained by nadir directed camera are georeferenced using the digital elevation model of the region, interior and exterior camera parameters. The digital elevation model is used to correct the relief displacement. The stereo-pair image is obtained when the UAV flies 200 m and image coordinates of the common control points are detected by colinearity equations. Position and orientation of UAV is corrected by least square adjustment and the process is repeated for each obtained image acquired at 200 m interval. The analysis revealed that the precisions of horizontal and vertical positioning becomes 75 and 200 meter, respectively. The precision of roll angle becomes worse than 0.5 degree, while the precisions of pitch and yaw angle are estimate to be better that 0.1 degree.

Modified depth map post-processing method for problems of accident-free UAV driving in urban infrastructure

Formulation of the problem. Currently, unmanned aerial vehicles (UAVs) are actively used to solve cross-industry tasks, such as photo and video filming of the surrounding space, remote analysis of surrounding objects, cargo delivery, monitoring the state of transport routes and mining complexes. UAVs are also used in emergency areas where the presence of people is associated with a threat to life. Since good orientation in space is necessary in all of these areas, UAV orientation in urban infrastructure is of great practical importance. For example, for accident-free driving of UAVs, determining the distance to obstacles (image depth maps) and constructing the trajectory of their flight is of great importance, which is relevant for precise UAV orientation in urban infrastructure. Target. Propose a modified method for post-processing the image depth map for the problems of accident-free driving of UAVs in urban infrastructure. Results. Existing methods and algorithms for converting from 2D signals to 3D signals in image analysis and display systems are considered. A study of the method of post-processing of the image depth map was carried out and its modification was proposed. To evaluate the effectiveness of the developed post-processing method, a comparative analysis of depth maps for various test images obtained by the original method and its modification was performed. Root-mean-square errors are obtained for the proposed and original post-processing methods for the considered test images. Practical significance. The presented modified image depth map post-processing method makes it possible to build sharper image depth maps, which provides more accurate UAV orientation in urban infrastructure.

Model-Based Optimization Approach for PID Control of Pitch–Roll UAV Orientation

This study focuses on the modeling and control optimization of the pitch–roll angles orientation in a quad-rotor UAV (unmanned aerial vehicle) drone system. To address the control challenge, PID (proportional–integral–derivative) controllers are used, which have been tuned through a model-based optimization approach. A non-linear model of the system is obtained and further validated experimentally. The model is implemented in Simulink to conduct model-based optimization. The controller design uses an IMC (internal model control) model-based approach to establish the initial parameters for a PID controller. In the subsequent design phase, a multiobjective approach is taken, incorporating weighted cost functions that account for IAE (integral absolute error) and ITAE (integral of time-weighted absolute error) forms, along with battery usage. The outcomes of this design are showcased through simulations and real-world platform testing.

КЛАССИФИКАТОР БПЛА МУЛЬТИРОТОРНОГО ТИПА

This article discusses a classifier of radar signals reflected from unmanned aerial vehicles(UAVs), based on neural networks. In the proposed classifier, for the formation of training data, a modelof scattering of radar signals from UAVs is used. Recently, the demand for UAV classification hasbeen quite high due to a significant increase in the number of models and sales of these devices. Increasingthe computing power of processors and the development of the theory of neural networks allows youto create new types of classifiers. When using models, it is possible to create a set of training data that isacceptable for training a classifier neural network. The convolutional neural network of the classifier istrained using radar images obtained using the proposed model of scattering of radar signals fromUAVs. The resulting radar images are modeled taking into account the UAV orientation angles relativeto the UAV normal coordinate system, flight speed, and various propeller parameters of the simulatedUAV. To form training data, in addition to the signal structure, white noise of a certain configuration isadded, which helps to increase the diversity of training samples to improve the learning ability of theconvolutional neural network. The use of data obtained using the model for training a neural network isdue to the need to use a large number of training samples with various UAV movement parameters,such as height, speed, direction, orientation in space, as well as a wide variety of possible configurationsof unmanned aerial vehicles: tricopter (three propellers), quadcopter (four propellers), hexacopter(six propellers), or octocopter (eight propellers). which complicates the use of experimental data tocreate classifiers of this type.

Определение изменений траектории и ориентации беспилотных летательных аппаратов по перекрывающимся снимкам

The article considers a method for determining abnormal changes in the trajectory and orientation of unmanned aerial vehicles in the conditions of loss of signals from satellites in the interests of improving the accuracy of navigation support for their exit to a given point of the horizontal flight route. The developed technique is based on the functional relationship of the difference in parallaxes of adjacent pairs of images obtained by the onboard camera of unmanned aerial vehicles during flight, with their deviations from the horizontal trajectory and changes in orientation. The obtained analytical relations allow for each corresponding point of a pair of images to form and solve a system of two nonlinear equations with five unknowns, which use deviations of unmanned aerial vehicles in altitude and direction of flight and their pitch, roll and yaw angles, approximate values of which are determined by the inertial navigation system. The procedures for the refinement of these parameters based on the math-ematical processing of the measurement results of the plane coordinates of the corresponding points by the method of least squares are presented. The proposed approach makes it possible to halve the minimum number of processed points and ensures the accuracy of determining the deviations of unmanned aerial vehicles from the horizontal trajectory and changes in its angular orientation, commensurate with the accuracy of satellite navigation.

Design of an Embedded Icosahedron Mechatronics for Robust Iterative IMU Calibration

Applications of low-cost microelectromechanical systems inertial measurement units (IMUs) have broadened over the past few years. Currently, IMUs are implemented in a wide variety of consumer electronics such as smartphones, smartwatches, and augmented reality/virtual reality (AR/VR) devices to detect human poses and real-time orientation of unmanned aerial vehicles. However, in order to precisely monitor objects’ poses, calibration of the IMU is crucial. In most cases, calibration procedures are conducted under a clean and perturbation free environment. However, such ideal environments and conditions may not always be available. Moreover, expensive and heavy calibration systems are usually required and unaffordable for general users. As a result, in this article, a low-cost, lightweight, and portable IMU calibration embedded icosahedron platform is developed. Since a clean calibration environment cannot be guaranteed, a calibration algorithm, with the consideration of external perturbations, is presented. An iterative weighted Levenberg–Marquardt algorithm is proposed to cope with perturbations. The highly integrated hardware/software codesign provides user-friendly operations for IMU calibration. Finally, simulations, as well as experiments, are presented to demonstrate the effectiveness and robustness of the proposed system.

UAV Landing Aid Hexapod Robot based on ArUco Marker and Sparse Optical Flow

A UAV (Unmanned Aerial Vehicle) landing robot system based on a six-degree-of-freedom hexapod and computer vision with ArUco marker and sparse optical flow is implemented in this paper. By using binocular camera measuring the real-time position and orientation of UAV, a dynamic target tracking method based on ArUco marker and sparse optical flow is proposed. In this method, the ArUco marker is combined with sparse optical flow to improve the accuracy of target detection and the matching error of binocular stereo matching. The binocular vision system with ArUco marker is used to measure and calculate the relative coordinates of markers in the camera coordinate system. Then the UAV contour fitting is conducted in order to obtain the real-time position and orientation of this mobile target. The effectiveness of the novel UAV landing hexapod robot system based on ArUco marker combined with sparse optical flow is verified through the UAV capture experiment.

On the construction of ultraviolet communication line and orientation for controlling a small unmanned aerial vehicle

The purpose of this work is to analyze methods for constructing an ultraviolet (UV) communication line and orientation for controlling a small unmanned aerial vehicle (UAV). In conditions of difficult terrain, the passage of radio waves is difficult, so it is necessary to use the optical range for communication and orientation. In the UV range, optical interference is significantly reduced and it is possible to create small-sized film antennas for UAVs. The characteristics of UV communication using film fluorescent antennas and multi-crystal semiconductor emitters are given. The UAV orientation method using onboard film antennas has been analyzed.

Attitude-Induced error modeling and compensation with GRU networks for the polarization compass during UAV orientation

The polarization compass used for unmanned aerial vehicle (UAV) navigation is usually hypothesized to be arranged horizontally in conventional heading measurement, which leads to a noticeable heading error due to the inevitable tilts called the pitch angle and the roll angle during UAV flight process. In addition, we found that the coupling of the angle between the solar meridian and the body axis of a carrier (A-SMBA) and tilted-angles will produce more remarkable heading errors. Consequently, we first introduce a comprehensive analysis of heading error in terms of variable attitude angles of the compass including the A-SMBA, the pitch angle and the roll angle. A novel heading error modeling and compensation for attitude-changed of the polarization compass by gated recurrent unit (GRU) neural network is developed subsequently. The experimental results demonstrate the proposed heading error modeling and compensation method performs best compared to state-of-the-art algorithms in predicting the UAV orientation.

3D Placement and Orientation of mmWave-Based UAVs for Guaranteed LoS Coverage

Unmanned aerial vehicles (UAVs), as aerial base stations, are a promising solution for providing wireless communications, thanks to their high flexibility and autonomy. Moreover, emerging services, such as extended reality, require high-capacity communications. To achieve this, millimeter wave (mmWave), and recently, terahertz bands have been considered for UAV communications. However, communication at these high frequencies requires a line-of-sight (LoS) to the terminals, which may be located in 3D space and may have extremely limited direct-line-of-view (LoV) due to blocking objects, like buildings and trees. In this letter, we investigate the problem of determining 3D placement and orientation of UAVs such that users have guaranteed LoS coverage by at least one UAV and the signal-to-noise ratio (SNR) between the UAV-user pairs are maximized. We formulate the problem as an integer linear programming(ILP) problem and prove its NP-hardness. Next, we propose a low-complexity geometry-based greedy algorithm to solve the problem efficiently. Our simulation results show that the proposed algorithm (almost) always guarantees LoS coverage to all users in all considered simulation settings.

Performance analysis of FSO based inter-UAV communication systems

Recently unmanned aerial vehicles (UAVs) gained considerable attention for recent potential applications like 6G, internet of things, disaster management applications etc. Especially inter UAV communications have an increased interest in low, medium, and high altitude platforms. Free space optical (FSO) communication plays a vital role in UAV communication to offer a high data rate, wider bandwidth, and secure transmission. In this paper, first time we introduced heterodyne detection (HD) in FSO based inter UAV communication. The outage and average bit error rate (BER) performance of the proposed system is analyzed and the results are compared with the existing Intensity modulation direct detection (IM/DD). We studied the impact of turbulence and pointing errors on BER and outage performance of the proposed system. The results are plotted for different system parameters such as Rytov Variance, field-Of-view, Transmitter UAV orientation ; receive UAV orientation, link range, and Beam width. The analytical results are validated with the monte-carlo simulations.

АНАЛИЗ ФАКТОРОВ ВЛИЯЮЩИХ НА СОСТАВ СИСТЕМЫ УПРАВЛЕНИЯ БЕСПИЛОТНОГО ЛЕТАТЕЛЬНОГО АППАРАТА

In this article the factors influencing the composition of an unmanned aerial vehicle (UAV) control system are considered. The given examples of management, are traditional ways of realization of a control system of the UAV orientation and are used in manysystems. Thus, the control system allows receiving and executing commands of the controller and providing stabilization of the aircraft for the specified parameters of speed, direction and altitude.

Improvement in energy conversion for unmanned aerial vehicle charging pad

<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 & 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>

Downlink Throughput Maximization in Multi-UAVs Networks Using Discrete Optimization

Unmanned Aerial Vehicles (UAVs) require frequent transmissions to a ground station. In this paper, we consider Time Division Multiple Access (TDMA) and equip the ground station with a Successive Interference Cancellation (SIC) radio, and thereby, allowing it to receive multiple transmissions simultaneously. A key problem is to identify a suitable TDMA transmission schedule that allows UAVs to transmit successfully and frequently to the ground station. Moreover, in order for SIC to operate, there must be a sufficient difference in received power at the ground station. However, in practice, due to the mobility and orientation of UAVs, the ground station experiences random channel gains. To this end, we adopt a discrete optimization approach to select a transmission schedule that yields the highest expected number of successes against random channel gains. We prove our approach is able to find the optimal transmission schedule. In addition, we propose a novel heuristic approach to generate a subset of transmission schedules for use in large-scale UAV networks. Our results show both proposed approaches yield high throughput under various network conditions. The average number of successful transmissions for schedules generated by our solutions is greater than 70%. In contrast, a competing approach only has an average success rate of less than 50%. Lastly, we conducted a trace-based simulation using data from a testbed with three static or mobile UAVs. Our results show that using a transmission schedule where at most two UAVs transmit yields more transmission successes.

Performance comparison of particle swarm optimization and Cuckoo search for online route planning

The popularity of unmanned aerial vehicles (UAV) has been constantly increasing during the last years. After being used as war tools by armies around the world, UAVs started being used in multiple civil applications. In the near future, hundreds or even thousands of UAVs will share the airspace with civil and commercial aviation [1]. Hence, UAVs become a new risk factor to consider in aerial security [2]. In this context, the need for researching and developing new intelligent systems capable of reducing the risks is justified. These intelligent systems must be able to optimize and update their flight trajectories to avoid collisions with buildings, mountains, or other airships. Therefore, the route planning method has real-time requirements. It must obtain the UAV orientation in real time, not only to reach the target but also to avoid collisions. The problem increases when the environment changes dynamically or when there is not a predefined flight route to follow [3].

Unmanned Aerial Vehicle (UAV) based mapping in engineering geological surveys: Considerations for optimum results

UAVs have been used in engineering for at least two decades, mainly focusing on structural health monitoring, geological surveys and site inspections, especially at cases where a rapid assessment is required, for example after a natural disaster. While there is a wide range of recognition algorithms for the automatic identification of structural damage, structural geological features etc. from the acquired images, the parameters affecting the resolution of these images are often overlooked. As a result, the UAV technology is not used at its full potential and at times, it is even regarded as leading to poor outcomes. This paper discusses the main parameters affecting the resolution of the images acquired by a UAV. We present a case study of the structural geological mapping of a coastal area carried out using two types of UAVs: a fixed wing and a hexacopter. A comparison between the structural geological maps based on the orthophotos and one produced using conventional techniques shows that the level of detail is the same and the time spent is at least 5 times less when using a UAV. The fixed wing is faster and therefore, can cover large areas while the copter gives better resolution images as it can fly at lower heights. The latter is cost and time effective only if it is used for surveys limited to small areas. The characterization of some structural geological features has not been possible based solely on the orthophotos. We show that in order to achieve the desired accuracy, a ground sample distance of at least half that value is required. We discuss technical aspects, such as the effect of topography and UAV orientation on the overlap value, the camera calibration, number of control points and lighting conditions, that should be taken into account prior to flying a UAV and provide recommendations on how to obtain optimum results, i.e. orthophotos that suit the needs of the project.

THE PREDICTION OF POSITION AND ORIENTATION PARAMETERS OF UAV FOR VIDEO IMAGING

Abstract. The paper presents the results of the prediction for the parameters of the position and orientation of the unmanned aerial vehicle (UAV) equipped with compact digital camera. Issue focus in this paper is to achieve optimal accuracy and reliability of the geo-referenced video frames on the basis of data from the navigation sensors mounted on UAV. In experiments two mathematical models were used for the process of the prediction: the polynomial model and the trigonometric model. The forecast values of position and orientation of UAV were compared with readings low cost GPS and INS sensors mounted on the unmanned Trimble UX-5 platform. Research experiment was conducted on the preview of navigation data from 23 measuring epochs. The forecast coordinate values and angles of the turnover and the actual readings of the sensor Trimble UX-5 were compared in this paper. Based on the results of the comparison it was determined that: the best results of co-ordinate comparison of an unmanned aerial vehicle received for the storage with, whereas worst for the coordinate Y on the base of both prediction models, obtained value of standard deviation for the coordinate XYZ from both prediction models does not cross over a admissible criterion 10 m for the term of the exactitudes of the position of a unmanned aircraft. The best results of the comparison of the angles of the turn of a unmanned aircraft received for the angle Pitch, whereas worst for the angles Heading and Roll on the base of both prediction models. Obtained value of standard deviation for the angles of turn HPR from both prediction models does not exceed a admissible exactitude 5° only for the angle Pitch, however crosses over this value for the angles Heading and Roll.

A UAV for bridge inspection: Visual servoing control law with orientation limits

This paper describes the dynamics of an unmanned aerial vehicle (UAV) for monitoring of structures and maintenance of bridges. It presents a novel control law based on computer vision for quasi-stationary flights above a planar target. The first part of the UAV's mission is the navigation from an initial position to a final position in an unknown 3D environment. The new control law uses the homography matrix computed from the information obtained from the vision system. The control scheme will be derived with backstepping techniques. In order to keep the camera's field of view, the control law uses saturation functions for bounding the UAV orientation and limiting it to very small values.

A UAV for bridge's inspection: visual servoing control law with orientation limits

This paper describes the dynamics of an Unmanned Aerial Vehicle (UAV) for monitoring of structures and maintenance of bridges. It presents a novel control law based on computer vision for quasi-stationary flights above a planar target. The first part of the UAV's mission is the navigation from an initial position to a final position in an unknown 3D environment. The new control law uses the homography matrix computed from the information coming from the vision system. It will be derived with backstepping techniques. In order to keep the target in the camera's field of view, the control law uses saturation functions for bounding the UAV orientation and limiting it to very small values.