Developing Protocols for Using a UAV to Monitor Herd Health

Unmanned Aerial Vehicles (UAVs) have created safety problems for the publics. Assessments of the mental workload for UAV operations are essential to realize the causes of UAV accidents. To test the following hypotheses: i. mission difficulty in UAV operation affects both subjective and objective measures of mental workload; ii. mission difficulty affects number of failures in UAV operation. Fourteen male adults participated as UAV operators after attending a UAV training course. They performed four flight missions of different difficulty levels. During their flight missions, their heart rate and inter-beat interval (IBI) were collected. Upon completing each flight mission, the participants gave subjective ratings of mental workload using three commonly adopted assessment tools. The time of flight and number of failures in flight operations were also recorded. The results showed that mission difficulty affected the scores of all three assessment tools significantly. Mission difficulty also affected number of failures and IBI significantly. The scores of the three assessment tools were highly correlated (ρ= 0.7 to 0.83, p < 0.001) with one another. The results of the three subjective ratings were also consistent with that of the IBI data. High mental workload in UAV operation could lead to poor flight performance.

Introduction. Due to their unique properties, unmanned aerial vehicles (UAVs) are widely used in the civil and military sectors. Due to the growing demand for specialist UAV operators, there is an increasing need to assess the working conditions at the workplaces of UAV operators. At the same time, special attention is paid to the sanitary and hygienic control of microbial contamination of the controls of unmanned vehicles. The study aims to execute a microbiological assessment of the qualitative and quantitative composition of microorganisms polluting the controls of unmanned aerial vehicles in order to further develop preventive measures aimed at preventing the spread of infectious diseases among operators of unmanned aerial vehicles. Materials and methods. The study assessed the quantitative and qualitative composition of microorganisms on control panels, keyboards, video cameras and video helmets of operators of unmanned aerial vehicles using both personal and multi-user equipment. Results. As a result of the study of microbial contamination of control panels, keyboards, video glasses and video helmets of operators of unmanned aerial vehicles, it was found that when operating equipment in multiuser access mode, the level of microbial contamination increases 2.9 times compared with personal use. In the course of the study, experts identified and ranked the main types of microorganisms living on the surfaces of video glasses, video helmets, keyboards and control panels of operators of unmanned aerial vehicles, with the aim of further developing and improving measures to preserve and promote the health of the aforementioned specialists. Limitations. It is necessary to study the effectiveness and safety of various disinfection methods for materials (plastic, glass, rubber, etc.) used to create UAV controls. To date, the impact of the use of glasses and helmets on the visual organ of operators of unmanned aerial vehicles in the long term of their use in the professional activities of specialists has not been fully studied, which does not allow fully assess the risks to their health. It is necessary to develop new solutions to minimize the impact of adverse factors on the organ of vision, including microbiological ones, as well as to minimize the manifestations of conjunctival symptoms. Conclusion. Multiuser equipment is most susceptible to microbial contamination, which increases the risk of infectious and inflammatory diseases among UAV operators. When using glasses and helmets, there are more pronounced manifestations of conjunctival symptoms due to their closer location to the organ of vision and the presence of additional fans in their design. The spectral composition of microorganisms contaminating UAV controls is mainly represented by representatives of opportunistic flora. The leading reason for contamination of equipment by opportunistic and pathogenic microorganisms is the limitation of the ability of UAV operators to comply with personal hygiene rules and insufficient treatment of equipment with disinfectant solutions. Ethics. The study was approved at a meeting of the Independent Ethics Committee at the Kirov Military Medical Academy on December 17, 2024 (Protocol No. 297 dated December 17, 2024). The study was conducted in compliance with ethical principles and the voluntary consent of the participants.

Wireless communication is an essential technology to unlock the full potential of unmanned aerial vehicles (UAVs) in numerous applications and has thus received unprecedented attention recently. Although technologies such as direct link, WiFi, and satellite communications are still useful in some remote scenarios where cellular services are unavailable, it is believed that exploiting the thriving 5G and beyond cellular networks to support UAV communications is the most promising and cost-effective approach, especially when the number of UAVs grows dramatically. On the one hand, to guarantee safe and efficient flight operations of multiple UAVs, it is of paramount importance to provide secure and ultra-reliable communication links between the UAVs and their ground pilots or control stations for conveying command and control signals, especially in beyond-visual-line-of-sight (BVLOS) scenarios. On the other hand, because of advances in communication equipment miniaturization as well as UAV manufacturing, mounting compact and lightweight base stations (BSs) or relays on UAVs becomes increasingly feasible. This has led to two promising research paradigms for UAV communications, namely, UAV-assisted cellular communications and cellular-connected UAVs, where UAVs are integrated into cellular networks as aerial communication platforms and aerial users, respectively. As such, integrating UAVs into cellular networks is believed to be a win-win technology for both UAV-related industries and cellular network operators, which not only creates plenty of new business opportunities but also benefits the communication performance of 3-D wireless networks. In addition, UAV related sensing and computing are also helpful for achieving efficient and reliable communication (e.g., in avoiding coverage holes) as well as smart UAV coordination, positioning, and trajectory design. However, 5G and beyond wireless networks with UAVs significantly differs from traditional communication systems, because of the high altitude and high maneuverability of UAVs, the unique UAV-ground channels, the diversified quality of service (QoS) requirements for downlink command and control (C&C) and uplink mission-related data transmission, the stringent constraints imposed by the size, weight, and power (SWAP) limitations of UAVs, as well as the new design degrees of freedom enabled by joint UAV mobility control and communication resource allocation.

The future of low altitude urban airspace utilization is poised to be transformed by the increasing dominance of small Unmanned Aerial Vehicles (UAVs). Their application can essentially be categorized as a threefold problem: establishing the regulatory principles for UAV operation, identification of the infrastructure needed to monitor the UAVs and ensure they adhere to the rules, and laying out the minimum performance requirements of the platforms so that they are capable of meeting the flight standards. This work addresses the pressing challenge of enhancing the performance envelope of small UAVs. The primary aim of this research is to develop an innovative overactuated multirotor system that augments UAV maneuverability, fault tolerance and operational safety. A crucial aspect of this study is overcoming the inherent underactuation limitations in standard quadrotors. This challenge is addressed through active propeller tilting, investigated in-depth through extensive real-world flight tests and simulations. The developed quadrotor, aptly named QuadPlus, efficiently combines actuator redundancy and thrust vectoring via propeller rotation in a compact package, compared to its state-of-the-art counterparts. Furthermore, a cascade control methodology based on incremental control allocation is devised to ensure stable attitude and velocity tracking even in the presence of actuator saturation and external disturbances during flight operations. The study showcases the successful realization of the QuadPlus multirotor system with an impressive 12 degrees of freedom. The innovative design allows for independent bi-axial tilting of 115 ° and 180 ° about two perpendicular axes while keeping the mechanical complexity relatively low. Real-world flight tests demonstrate the efficacy of the control methodology, showcasing stable hover and trajectory tracking in a desired hyperplane with accurate attitude tracking. Different test cases demonstrating the capability of QuadPlus to achieve symmetric (20 ° roll and pitch) and asymmetric (20 ° roll, 10 ° pitch and vice versa) attitude with static hover are presented. It is also tested against Level 3 wind conditions of 4m/s and actuator saturation. The extensive bi-axial tilting capability of the system enables precise force production of up to 9N for contact-based tasks, presenting promising potential for inspection-related applications. The research also significantly contributes to ensuring fail-safe UAV operations. A centralized fault-tolerant control (FTC) framework based on nonlinear model predictive control (NMPC) is proposed to address potential propeller failures, effectively mitigating attitude deviations and enhancing overall system control. The FTC framework is validated through intensive simulations, proving its effectiveness in maintaining stable flight even in the presence of failures. The system is successfully tested against a single propeller failure while following an attitude of 30 ° each in roll and pitch. It is also successfully tested for failure recovery in aggressive flights following an 8-shaped trajectory with the attitude varying between ±30 ° for roll and pitch, and ±25 ° for yaw. The corresponding maximum deviations from the commanded trajectory are observed to be within acceptable limits. Additionally, the research introduces a novel approach for on-board state-of-health (SoH) diagnostics of the battery, a critical component of the multirotor system. The energy equilibrium approach enables better management of battery performance, ensuring safe and reliable UAV operations while avoiding rapid performance deterioration. Experimental work is performed to validate the model. However, further analysis onboard QuadPlus is presented as future work as part of realizing the fault tolerance capabilities. It is hypothesized that the integration of the SoH diagnostics into the flight controller will help keep the current drawn within the safe functional limits of the battery. In summary, this research substantially advances the field of UAV technology by presenting a groundbreaking solution to the challenges posed by low altitude urban airspace utilization. The innovative overactuated multirotor system, QuadPlus, coupled with the fault-tolerant control framework and on-board component diagnostics approach, holds immense potential for inspection-related applications and interactions with the physical environment.

Operator Engagement During Prolonged Simulated UAV Operation

Objective: The aim of the article is to present the state of the art on threats to UAVs posed by sudden changes of weather conditions, involving in particular storms and hail. Identifying such threats is likely to facilitate the development of hardware and software solutions aimed at improving the safety of the UAV missions. Introduction: Severe weather phenomena strongly affect the safety of unmanned aerial vehicle (UAV) missions. The article describes in detail the implementation concept of atmospheric discharge and precipitation images using wireless Internet connections for an exemplary mobile application for multi-rotor flight control. The concept was developed to reduce risks associated with flights in storm and precipitation areas, and to maximise the performance of electric multi-rotor UAVs with a maximum take-off mass of no more than 25 kg. This is dealt with in the introductory section and in three substantive sections. UAV capabilities are discussed in the first section, while the second one analyses specific weather conditions which merit particular attention when constructing new UAVs, and the third one outlines some of the solutions employed in UAV steering systems control apps. A number of concluding remarks are presented in the end. Conclusions: The analysis of usefulness has proven electric UAVs suitability for professional missions. However, these vehicles display a number of limitations, one of the most important being their high sensitivity to weather conditions. With no hermetically sealed hatch, on-board equipment is exposed to penetrating damp caused by various types of precipitation, including drizzle, rain and snow. These can cause a short-circuit and equipment damage, while hailstones can result in UAV mechanical damage. Severe turbulences and strong ascending or descending air currents, which are likely to occur during low-altitude flights, pose a threat of UAV's collision with overground objects. Using more resistant composite materials in the construction of hermetic UAVs could increase the application range of these vehicles. The wide range of possible uses of UAVs encourages further investigations aimed at ensuring their best possible working conditions.

Over the past decade the use of Unmanned Aerial Vehicles (UAVs) for the inspection of turbine blades has been registering steady progress and is fast becoming a well-established inspection methodology especially at offshore wind farms. A UAV operating in the open field is subject to varying ambient conditions which have an effect on the power required to maintain stable flight. This may have an impact on the flight endurance of the UAV, especially when operating in windy conditions. Simulations are a very useful tool for estimating the impact of such ambient conditions on the performance and flight endurance of a UAV. However, it is extremely difficult to accurately model all the dynamics at play in the open field where flow conditions are highly stochastic. Few open field studies necessary to validate such simulation models have been carried out to date in this regard. In this study, the impact of open field wind conditions on the flight endurance of a hovering UAV is investigated. The test vehicle used in this study is a quadrotor UAV, which was fitted with an array of sensors to monitor power consumption parameters of the propulsion motors whilst the vehicle is hovering at a fixed altitude above the ground. The quadrotor was also fitted with an ultrasonic wind sensor in order to measure the relevant wind parameters that the quadrotor was being subjected to during the hovering study. The test UAV was flown in different ambient conditions to establish the impact on the UAV flight endurance when subjected to different wind speeds. Results from a series of UAV test flights in the open field indicated that the power required by the UAV to maintain hovering flight decreases as the wind speed increases.

In this paper a multiple object detection, recognition, and tracking system for unmanned aerial vehicles (UAVs) has been studied. The system can be implemented on any UAVs platform, with the main requirement being that the UAV has a suitable onboard computational unit and a camera. It is intended to be used in a maritime object tracking system framework for UAVs, which enables a UAV to perform multiobject tracking and situational awareness of the sea surface, in real time, during a UAV operation. Using machine vision to automatically detect objects in the camera's image stream combined with the UAV's navigation data, the onboard computer is able to georeference each object detection to measure the location of the detected objects in a local North‐East (NE) coordinate frame. A tracking algorithm which uses a Kalman filter and a constant velocity motion model utilizes an object's position measurements, automatically found using the object detection algorithm, to track and estimate an object's position and velocity. Furthermore, a global‐nearest‐neighbor algorithm is applied for data association. This is achieved using a measure of distance that is based not only on the physical distance between an object's estimated position and the measured position, but also how similar the objects appear in the camera image. Four field tests were conducted at sea to verify the object detection and tracking system. One of the flight tests was a two‐object tracking scenario, which is also used in three scenarios with an additional two simulated objects. The tracking results demonstrate the effectiveness of using visual recognition for data association to avoid interchanging the two estimated object trajectories. Furthermore, real‐time computations performed on the gathered data show that the system is able to automatically detect and track the position and velocity of a boat. Given that the system had at least 100 georeferenced measurements of the boat's position, the position was estimated and tracked with an accuracy of 5–15 m from 400 m altitude while the boat was in the camera's field of view (FOV). The estimated speed and course would also converge to the object's true trajectories (measured by Global Positioning System, GPS) for the tested scenarios. This enables the system to track boats while they are outside the FOV of the camera for extended periods of time, with tracking results showing a drift in the boat's position estimate down to 1–5 m/min outside of the FOV of the camera.

For the large-scale operations of unmanned aerial vehicle (UAV) swarm and the large number of UAVs, this paper proposes a two-layer task and resource assignment algorithm based on feature weight clustering. According to the numbers and types of task resources of each UAV and the distances between different UAVs, the UAV swarm is divided into multiple UAV clusters, and the large-scale allocation problem is transformed into several related small-scale problems. A two-layer task assignment algorithm based on the consensus-based bundle algorithm (CBBA) is proposed, and this algorithm uses different consensus rules between clusters and within clusters, which ensures that the UAV swarm gets a conflict-free task assignment solution in real time. The simulation results show that the algorithm can assign tasks effectively and efficiently when the number of UAVs and targets is large.

The article identifies the conditions and factors that will affect the operation of unmanned aerial vehicles during its use in emergencies. The purpose of the study is to systematize the conditions and factors that will affect the functioning of specific technical means of surveillance installed on the unmanned aerial vehicle. The study of conditions and factors was carried out with a preliminary determination of the general indicators of efficiency of specific technical means of observation installed on the drone, which include: the probability of detection and recognition of the object by the operator (pilot-operator) on the display screen; the scale of the image on the display screen; viewing angle of the species technical means of observation; transverse capture of the area during aerial surveillance with the help of specific technical means; spectral range of operation of the species technical means of observation and the height of observation. According to the results of research, the conditions and factors include: unmanned aerial vehicle; set task for observation (monitoring); terrain features; control by the pilot (pilot-operator); weather conditions; gusts of wind; season; time of day; drone vibrations during flight; atmospheric turbulence; control of specific technical means of observation by the operator (pilot-operator); temperature regime; the presence of a library of signatures of the object of observation. It is concluded that the results of the study of conditions and factors that will affect the use of specific technical means of observation installed on an unmanned aerial vehicle are the basis for developing relevant requirements for specific technical means of observation of visible and infrared wavelengths of the electromagnetic spectrum. Further research should be carried out in the following areas: development or purchase of unmanned aerial vehicles for observation during the prevention and elimination of emergencies; development of libraries of signatures of objects of observation; research of possibilities of application of spectrozonal or multispectral species equipment for observation; creation of special training grounds for training and retraining of pilots and operators of unmanned aerial vehicles, etc.

The proliferation of unmanned aerial vehicles (UAVs) has driven the emergence of urban air mobility (UAM) as a solution to alleviate the increasing demand for UAVs applications in various domains. The concept of UAM envisions a future where UAVs play a pivotal role in short-distance transportation, delivery services, surveillance, emergency rescue, and more. However, the rapid growth of UAVs poses significant challenges arising from the need to ensure the safe coexistence of UAVs with other manned/unmanned aerial vehicles. To ensure the safe integration of UAVs into low-altitude urban airspace and support high-density on-demand mobility, this research focuses on handling the safety-centric challenges related to UAV collision risk assessment, obstacle avoidance, and conflict resolution in complex urban environments.&#13;\nOne of the main challenges is the intrusion of UAVs into airport runways. Airports serve as critical hubs for civil aircraft takeoff and landing operations. However, the increasing presence of UAVs has raised concerns about intruding into airports, leading to flight delays and temporary runway closures. To quantify the potential interference of UAVs on civil aircraft, a collision-course based trajectory planning model is proposed to evaluate the collision risk between manned civil aircraft and intruding UAVs. In this risk assessment model, the trajectory of the intruding UAV is formulated using a collision-course concept, taking into account the limited trajectory information available about intruding UAVs. The planned trajectory of the UAVs is then used to predict its relative position concerning civil aircraft. To account for the possible disturbances of the relative distance, a stochastic position prediction model based on Brownian motion is developed. The collision risk is assessed based on this stochastic kinematic model, providing a quantitative measure of the potential collisions. The proposed model is validated through extensive simulations involving different UAV initial positions, position updates, and different sizes of collision zone tests, as well as comparative tests with the Monte-Carlo algorithm, demonstrating its robustness in assessing the collision risk of the airport restricted area. To facilitate the application, the model is finally used to develop a platform to generate runway heatmaps, accounting for airport runway risk distributions. &#13;\nAnother safety-centric challenge is ensuring autonomous obstacle avoidance and conflict resolution of UAVs. To enable UAV autonomous safe operations in uncontrolled urban low-altitude airspace, a comprehensive collision-free path planning framework is developed to address the avoidance of both static obstacles and dynamic threats. Firstly, to handle static obstacles, a novel algorithm of 3D voxel jump point research is introduced to generate a global reference path for UAV navigation to avoid static obstacles, particularly for a free flight at different altitudes. Additionally, to optimize the reference path for specific mission requirements, techniques such as trajectory de-diagonalization, reconstruction, and smoothness are proposed to reduce the risk of static collisions, shorten the fly range, and enable UAVs to negotiate turns more efficiently. Secondly, real-time conflict resolution actions based on the Markov decision process are developed to avoid local dynamic threats encountered along the optimized desired path. This allows the host UAV to dynamically adjust its course to a resolution trajectory while maintaining its planned speed without hovering to avoid the potential collision with the approaching intruders. By avoiding near mid-air collisions (NMAC) and preventing the UAV from hovering, the proposed method ensures the timely completion of UAV missions. Simulation results demonstrate that the developed method successfully achieves UAV autonomous global path planning and local real-time conflict resolution in complex urban low-altitude environments, thereby avoiding both static obstacles and dynamic threats. &#13;\nMoreover, to bridge the research gap of UAV hard conflict resolution in mitigating NMAC risks arising from local dynamic threats, a novel situational NMAC risk assessment approach is developed by integrating the conditional random field (CRF) algorithm with safety metrics and conflict resolution performance to facilitate UAV tiered aerial passage operations. To improve UAV operating environments in urban airspace, a concept of tiered aerial passages is first designed to provide a practical urban airspace planning scheme that addresses UAV heterogeneity and optimizes the utilization of urban airspace. For UAV tiered aerial passage operations, a situational NMAC risk assessment module coupled with a conflict resolution decision-making module is formulated, enabling the host UAV to evaluate and respond to real-time conflicts, ensuring avoidance of potential collisions. To assess NMAC risks, a general risk assessment model is proposed based on the CRF algorithm, considering UAV safety metrics and resolution performance. Then the overtaking, approaching head-on, and converging UAV encounters are analyzed, and situational risk potential scores are created using the Gaussian kernel function in the CRF algorithm, considering advisory, caution, and warning risk alert levels. To resolve conflict, acceptable, tolerable, and unacceptable scenarios are proposed to enhance the flexibility and personalization of the resolution decision-making. The proposed scheme is validated by simulating geometric encounter situations and comparative tests with the previous hard resolution technique. The results indicate that the proposed method outperforms UAV NMAC risk assessment and conflict resolution. Even in the most dangerous unacceptable resolution decision-making scenarios across three conflict encounters, the proposed algorithm achieves NMAC rates of 0.036, 0.070, and 0.043, which are lower than the corresponding NMAC rates associated with the hard resolution approach. Together with the acceptable and tolerable scenarios, the proposed negotiation resolution effectively tailors different risk requirements to accommodate diverse UAV missions. &#13;\nWith a primary focus on ensuring the safety of the UAM architecture, this research endeavors to assess UAV NMAC risks and efficiently manage potential conflicts. The proposed work are thoroughly validated to demonstrate their effectiveness in real-world scenarios. As a result, this study significantly contributes to the establishment of a robust UAM architecture, facilitating the realization of safe and reliable UAM.

Мета: Відсутність алгоритму рекомендацій дій оператора БПЛА в надзвичайних ситуаціях, розкладання процесу прийняття рішень оператором БПЛА в надзвичайних ситуаціях, розробка структури системи підтримки прийняття рішень для оператора БПЛА, розробка моделей прийняття рішень оператором БПЛА. Методи: Створення алгоритму прийняття рішень за допомогою критеріїв Вальда, Гурвіца, Ла Пласа. Результати: програма "UAV_AS", що дає рекомендації оператору БПЛА про те, як діяти в разі виникнення надзвичайної ситуації. Авторами розроблено алгоритм дій рекомендації оператора БПЛА в надзвичайних ситуаціях. Представлений процес прийняття рішень оператором БПЛА в надзвичайних ситуаціях у вигляді детермінованої моделі із застосуванням методів мережевого моделювання. Побудовано мережевий граф, за яким визначено критичний час на парирування надзвичайної ситуації у разі польоту БПЛА. Розроблено структуру розподіленої СППР для колективного управління пілотованих та безпілотних літальних апаратів оператором. Авторами розроблено бази даних для локальних СППР операторів управління БПЛА, Розроблено моделі прийняття рішень оператором БПЛА в умовах ризику та в умовах невизначеності у разі аварійної посадки БПЛА. Обговорення: У статті розглядаються проблеми польотів безпілотних літальних апаратів для вирішення різних завдань в надзвичайній ситуації, засноване на статистичних даних від аналізу типів надзвичайних ситуацій для безпілотних літальних апаратів. Визначається послідовність дій оператора БПЛА в разі виникнення надзвичайних ситуацій.

The paper investigates the aerodynamic performance and power requirement characteristics of wing sections integrated with high-lift airfoil to support the operation of solar-powered Unmanned Aerial vehicle (UAV). The flight mission is aimed to simulate the operation of solar-powered UAVs under low -speed environment. The research focuses on studying the aerodynamic effect of non-solar UAV wing model and solar UAV wing model for the varying angle of attack. The UAV wing models are tested using a subsonic wind tunnel to validate the aerodynamic characteristics at low-speed condition. The aerodynamic parameters such as coefficient of lift (Cl), coefficient of drag (Cd), coefficient of pressure (Cp), and the total power required to accelerate the solar UAV are studied to maintain steady level flight. The solar UAV and non-solar UAV wing models were subjected to a computational process to examine the pressure and velocity distributions for the aerodynamic performance analysis. Evident results show that the solar cells positioned at the flow separation region of the UAV wing model produces an aerodynamic efficiency rate of 5.45% and required 37.13W of minimum power compared to non-solar UAV at the Reynolds number of 9.8 106.

This paper presents a fine-grained decomposition of situation awareness (SA) as it pertains to the use of unmanned aerial vehicles (UAVs), and uses this decomposition to understand the types of SA attained by operators of the Desert Hawk UAV. Since UAVs are airborne robots, we adapt a definition previously developed for human-robot awareness after learning about the SA needs of operators through observations and interviews. We describe the applicability of UAV-related SA for people in three roles: UAV operators, air traffic controllers, and pilots of manned aircraft in the vicinity of UAVs. Using our decomposition, UAV interaction designers can specify SA needs and analysts can evaluate a UAV interface's SA support with greater precision and specificity than can be attained using other SA definitions.

A truck and drones model for last-mile delivery: A mathematical model and heuristic approach