Classes and Missions of UAVs

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.
\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. 
\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. 
\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. 
\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.

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.

The subject of this study is the current state and prospects for the development of the market for unmanned aerial vehicles (UAVs) and power plants. The purpose of this work was to identify trends in the development of UAV engines of various classes. Task: collection, systematization, and analysis of information on the most common engines of reconnaissance and strike UAVs of the operational-tactical level, as well as UAVs of the "barrage ammunition" class. This article provides a brief description of various types of UAV power plants, and their main advantages and disadvantages are given, which are often decisive when choosing the type of power plant for a specific UAV. It was found that a power plant with an internal combustion engine (ICE) is best suited for use in medium- and long-range UAVs.This study demonstrated that four-stroke internal combustion engines are most commonly used in reconnaissance-strike UAVs at both operational and tactical levels. The features of the design and characteristics of four-stroke internal combustion engines, which have become the most widely used UAVs, are described. It was determined that the introduction of turbocharging or increasing the pressure is the main means of forcing four-stroke internal combustion engines, which makes it possible to simultaneously achieve high specific power and high brake efficiency of the engine over a wide range of altitudes during its operation. It is shown that one of the most important tasks for a long-range UAV engine is to reduce the specific brake fuel consumption. Thus, there is a tendency to promote the use of high-powered aviation diesels in long-range UAVs. It was determined that the main requirements for UAV engines of the "barrage ammunition" class are high specific power, low cost and adaptability to mass production. This study shows that gasoline two-stroke internal combustion engines with crank-chamber scavenging are extremely widespread in UAVs of the "barrage ammunition" class. The design features and characteristics of UAV two-stroke internal combustion engines are described. The main means of ensuring high specific power of such two-stroke internal combustion engines are increasing the engine RPM, optimizing gas exchange processes, and reducing the weight of the construction by using new materials. Conclusion. The results show that depending on the UAV type, the set of engine requirements can vary significantly. Modern trends in the development of UAV engines of various classes have been determined. Potentially promising directions for increasing the efficiency of engines and for comprehensive improvement of their indicators and characteristics have been determined.

The current research represents a first step towards developing a decentralized network of small autonomous, intelligent and inexpensive unmanned aerial vehicles (UAV), which could be used for a variety of scientific missions where measurements from a distributed network of nodes could significantly improve the assessment. The paper presents an adaptive airborne sensing platform (e.g., UAV) that could be used to fuse the information acquired through multiple sensing modalities (obtained from sensors located close to or inside the phenomena) to monitor environmental processes over space and time. The sensing platform is able to continuously reconfigure its trajectory according to the circumstances (e.g., continuously evolving scientific phenomena) to optimize the location of individual sensing waypoints. As proof of concept and validation, we will apply the proposed sensing approach to monitoring volcanic plumes. The paper focuses on (i) developing a Bayesian statistical method to create sensor fusion algorithms that is used to model the plume and guide the UAV in an optimal way (ii) implementing a distributed task allocation scheme which is able guide all the UAVs efficiently and optimize the UAV paths for various criteria.

Radar surveillance of unmanned aerial vehicles (UAVs) is actively developing area of scientific research. This article provides a review and analysis of publications in recent years devoted to the methods and radar systems of detection and recognition of classes and types of UAVs. It is noted that the most difficult targets for radar detection are low-sized, low-speed small UAVs (drones) flying at low and extremely low altitudes. If large and medium-sized UAVs can be detected by modern radar systems, then for the detection of small UAVs it is advisable to create specialized highly efficient, highly mobile, portable and inexpensive active UAV detection radars. The technical requirements for such radars are defined and recommendations for their implementation are provided. High-performance protection systems based on adaptive lattice filters are offered to protect UAV detection radars from noise jamming and passive interference. It is shown that the research on the methods of recognizing UAV classes and types is a development of the existing theory and technology of radar recognition of air targets.

Small unmanned aerial vehicles (UAVs) have been widely used in different aspects of modern farming management, including pest and disease control in China in recent years. In this study, the spray performance of a small plant protection UAV at low volume spray was evaluated by adjusting the pesticide dosage and adding aerial spraying adjuvants. Droplet deposition, droplet density, coverage, control effect and pesticide residue from field trials were assessed. In addition, the residue and control effect of UAV spray were compared to manual knapsack at high volume spray. The results showed that, the adjuvant applying improved the efficiency of UAV spray. Also, the adjuvant applying reduced the dosage of imidacloprid by 20%. However, there was no significant difference on initial residue between UAV spray and knapsack spray. Thus, plant protection UAV spraying pesticide by adding appropriate adjuvant showed the ability of improving the pesticide effectiveness by improving the control efficiency, reducing the pesticide dosage and residue. Keywords: unmanned aerial vehicle (UAV), aerial spraying adjuvant, deposition, control efficiency, pesticide residue, wheat aphid DOI: 10.25165/j.ijabe.20181105.4298 Citation: Meng Y H, Lan Y B, Mei G Y, Guo Y W, Song J L, Wang Z G. Effect of aerial spray adjuvant applying on the efficiency of small unmanned aerial vehicle on wheat aphids control. Int J Agric & Biol Eng, 2018; 11(5): 46–53.

As the use of unmanned aerial vehicles (UAVs) in various commercial, civil, and military applications increases, it becomes important to study the design of aerial drone corridors that can support multiple simultaneous UAV missions. In this work, we study the placement of base stations (BSs) to serve aerial drone corridors while satisfying specific UAV mission requirements, such as the geometrical waypoints for the UAV to fly through and the minimum data rate to be supported along the mission trajectory. We develop a mathematical model of the drone corridor and propose a brute force algorithm that leverages A* search to meet the quality of service (QoS) requirements of the corridor by choosing the minimal set of BS locations from a pre-determined initial set. Using raytracing simulations, BS placement results are presented for various antenna array sizes in a dense urban region in East Manhattan. It was found that, for the scenario under consideration, a single BS equipped with an 8x8 antenna array is sufficient to satisfy the given QoS requirements of the corridor, while two BSs are required when using 4x4 antenna arrays.

The Integrated Modular Avionics (IMA) architecture has been suggested to address the Size, Weight, and Power (SWaP) issues and provide better software consolidation and testability by means of partitioning. Though the IMA architecture is mainly discussed from the view point of large aircrafts or manned aerial vehicles, small Unmanned Aerial Vehicles (UAV) are one that indeed requires IMA to reduce SWaP. In this study, we design and implement UAV control and mission software over ARINC 653. Especially we utilize our Linux-based ARINC-653, which can provide abundant development tools, software libraries, and device drivers due to the nature of Linux. Our control and mission software include Operational Flight Program (OFP), Video Streaming Program (VSP), Ground Control Program (GCP), and Ground Monitoring Program (GMP). We test our programs in a HILS environment and show that these run correctly in terms of functionality and real-time requirements. Our study also suggests few extensions for process scheduling and inter-partition communication of ARINC 653.

Nowadays, owing to the communication, computation, storage, networking, and sensing abilities, the swarm of unmanned aerial vehicles (UAV) is highly anticipated to be helpful for emergency, disaster, and military situations. Additionally, in such situations, each UAV generates local sensing data with its cameras and sensors. Data sharing in UAV swarm is an urgent need for both users and administrators. For users, they may want to access data stored on any specific UAV on demand. For administrators, they need to construct global information and situational awareness to enable many cooperative applications. This paper makes the first step to tackling this open problem with an efficient data-sharing framework called Frisbee. It first groups all UAVs as a series of cells, each of which has a head-UAV. Inside any cell, all UAVs can communicate with each other directly. Thus, for the intra-cell sharing, Frisbee designs the Dynamic Cuckoo Summary for the head-UAV to accurately index all data inside the cell. For inter-cell sharing, Frisbee designs an effective method to map both the data indices and the head-UAV into a 2-dimensional virtual plane. Based on such virtual plane, a head-UAV communication graph is formed according to the communication range of each head for both data localization and transmission. The comprehensive experiments show that Frisbee achieves 14.7% higher insert throughput, 39.1% lower response delay, and 41.4% less implementation overhead, respectively, compared to the most involved solutions of the ground network.

The main prospects for the group use of unmanned aerial vehicles (UAVs) were analyzed, the problems were identified, and the stages of its solution were proposed. The basic algorithms are analyzed, which are designed to achieve joint and coordinated actions of all elements of the system of integrated control of a group of UAVs, and are used in most approaches to ensure stable interaction between system components. The analysis of the most common mathematical models for controlling groups of UAVs was carried out, in particular: the Reynolds cohesion model, the artificial potential field model, and the leader-following model. The peculiarities of the operation of these models, common and distinctive features, advantages and disadvantages are determined. Based on the considered models and basic interaction algorithms, the algorithms of the components of the UAV group control system are proposed, and the sequence of actions during the interaction between the system components is also described. The main details of UAV group control algorithms are considered. The main aspects of the interaction of the system elements are given, which include messages of various categories used at different stages of the system's operation, in particular: synchronizing messages; group-wide control messages for managing the group as a whole; messages for correcting the flight of a specific UAV; notification of the transfer of statistical information for flight correction; notification of the launch and coordination of the task execution by a specific UAV. The use of joint messages for group management is described, which allows you to relieve the transmission channel, because the flight trajectories are calculated by each UAV individually, according to predetermined criteria. The main stages of the system's operation, the peculiarities of their implementation, the sequence of message transmission in each stage, as well as the basic details of the operation of some system components are described. Block diagrams are provided to display the process of system operation at various stages of flight, with a detailed description of the steps of system operation. The process of collecting statistical data from UAVs for dynamic flight adjustment of the group is described.

Parallel hybrid-electric propulsion systems would be beneficial for small unmanned aerial vehicles used for military, homeland security, and disaster-monitoring missions involving intelligence, surveillance, or reconnaissance (ISR). The benefits include increased time on station and range as compared to electric-powered unmanned aerial vehicles and reduced acoustic and thermal signatures not available with gasoline-powered unmanned aerial vehicles. A conceptual design of a small unmanned aerial vehicle with a parallel hybrid-electric propulsion system, the application of a rule-based controller to the hybrid-electric system, and simulation results are provided. The two-point conceptual design includes an internal combustion engine sized for cruise speed and an electric motor and lithium-ion battery pack sized for endurance speed. A rule-based controller based on ideal operating line concepts is applied to the control of the parallel hybrid-electric propulsion system. The energy use for the 13.6 kg (30 Ib) hybrid-electric unmanned aerial vehicle with the rule-based controller during one-hour and three-hour ISR missions is 54% and 22% less, respectively, than for a four-stroke gasoline-powered unmanned aerial vehicle.

U NMANNED aerial vehicles (UAVs) have been widely used in various services and are predicted to be extensively used in the near future [1–8]. In UAV applications, weather supporting plays a critical role at all echelons from control, navigation, and path planning to asset safety. Adverse weather conditions such as thunderstorms, icing, turbulence, and wind are great influences on UAVsafety andmission success. For instance, the Predator, deployed in the Balkans in the late 1990s, experienced lowmission-completion rates, with the primary factor being weather [9]. It is therefore imperative to incorporate weather forecasting into path planning. Past efforts have led to some weather support tools such as the Aviation Weather Routing Tool, the Integrated Weather Effects Decision Aid, and others [10]. The shortfalls of these tools are that they rely on deterministic forecasts [11] and ignore forecasting uncertainties. The recent development in numerical weather prediction [12–15] makes possible the high-resolution ensemble forecasting [16,17]. In ensemble forecasting, different weather models are performed many times in a stochastic mode with model inputs, initial conditions, and boundary conditions being slightly changed for each run. Each single run contains a different number of ensemble members and generates a prediction spectrum. This allows us to build an objective and stochastic weather forecast that supports statistical postprocessing [10,11,16,17]. Based on this information, a probabilistic weather map can be constructed. With continuous ensemble forecasting updating at a rate of once per time unit, this analysis provides an online four-dimensional (4-D) (with time as one dimension) weather map. From the 4-D weather map and a UAV mission, the planning algorithm is implemented to calculate waypoints describing the UAV route. In this research, a deterministic three-dimensional (3-D) field D* planning algorithm [18] is used to find the optimal flying route. The optimality of the route is evaluated on the metrics of execution time, mission risk, route distance, and fuel consumption. The structure of the overall system is shown in Fig. 1, which consists of weather-forecasting data, probabilistic analysis, forecasting update, map construction, and optimal mission planning.

A fuzzy logic resource manager that enables a collection of unmanned aerial vehicles (UAVs) to automatically cooperate to make meteorological measurements will be discussed. Once in flight no human intervention is required. Planning and real-time control algorithms determine the optimal trajectory and points each UAV will sample, while taking into account the UAVs' risk, risk tolerance, reliability, mission priority, fuel limitations, mission cost, and related uncertainties. The control algorithm permits newly obtained information about weather and other events to be introduced to allow the UAVs to be more effective. The approach is illustrated by a discussion of the fuzzy decision tree for UAV path assignment and related simulation. The different fuzzy membership functions on the tree are described in mathematical detail. The different methods by which this tree is obtained are summarized including a method based on using a genetic program as a data mining function. A second fuzzy decision tree that allows the UAVs to automatically collaborate without human intervention is discussed. This tree permits three different types of collaborative behavior between the UAVs. Simulations illustrating how the tree allows the different types of collaboration to be automated are provided. Simulations also show the ability of the control algorithm to allow UAVs to effectively cooperate to increase the UAV team's likelihood of success.

Unmanned aerial vehicles (UAVs) are rapidly increasing in popularity. Despite attempts at regulation, stopping small, Class 1 (typically hobby-grade) UAVs from entering protected or sensitive airspace is an unsolved problem. Many companies and researchers offer a piece of a solution, but as of this writing, there is no publicly available, feasible, end-to-end solution. Ultimately, what is needed is a sensor-based system that autonomously detects, tracks, and neutralizes/disables an incoming UAV. However, such a system is currently not available, so as development toward that goal continues, a temporary solution is required. Augmenting the skill, dexterity, and processing power of human pilots with inexpensive cameras and computer vision algorithms can offer such a solution. The foundations of a framework for a system that uses computer vision to target and ultimately destroy a target in mid-air is introduced. The proposed solution utilizes a light-weight, inexpensive UAV with an on-board camera. The detection and tracking is performed in real-time on a companion computer mounted to the frame of the vehicle, with ROS as the primary communication infrastructure. Initial simulations provide insight into the feasibility of using computer vision with a monocular camera to offer reliable assistance to the pilot.

This paper is a summary of experiments to assess alternative methods to control a small (<25 kg; under Transport Canada rules, small UAV are classified as under 25 kg; Transport Canada. 2014. TP15263 – Knowledge requirements for pilots of unmanned air vehicle systems (UAV) 25 kg or less, operating within visual line of sight. Transport Canada. August. Available from http://www.tc.gc.ca/eng/civilaviation/publications/page-6557.html [accessed 17 August 2015]) unmanned aerial vehicle (UAV) in manual mode. While it is true that the majority of a typical UAV mission will be in automatic mode (i.e., using an autopilot) this may not always be the case during takeoffs and landings, or if there is a failure of the autopilot. The concept of a manual control backup mode during all flight phases remains in proposed UAV regulations currently being defined in Canada and the US. The research summarized in this paper is an attempt to assess the accuracy of several manual control options for a small UAV. The paper includes both a theoretical discussion of the task of manually controlling a small UAV airframe and results from a series of field experiments investigating the use of first-person view techniques.