An Intuitive End-to-End Human-UAV Interaction System for Field Exploration.

Field determination of multipollutant, open area combustion source emission factors with a hexacopter unmanned aerial vehicle

<div class="section abstract"><div class="htmlview paragraph">The development of low-altitude economy driven by aircraft has garnered significant attention from both academia and industry. The hexacopter unmanned aerial vehicle (UAV) is an important component of low-altitude aircraft. Although it has not been as widely used as the quadcopter UAV, the greater delivery capacity and enhanced fault tolerance sustain its promising development prospects. However, the trajectory tracking control, a fundamental task of hexacopter UAV, remains challenging if the control algorithm is required to work on the dynamics level with theoretical performance guarantees, since its position control has to be realized by its attitude control. This study proposes a novel trajectory tracking control with prescribed performance for the hexacopter UAV that works on the dynamic model. The proposed approach is established by a dual-loop constraint-following control with the state-transformation technique, where equality and inequality constraints are used to describe the tracking task and the prescribed performance, respectively. The effectiveness of the proposed control is endorsed by rigorous theoretical analysis and simulations.</div></div>

Vertical profiles of aerosol light scattering (bscat), absorption (babs), as well as the single scattering albedo (SSA, ω), play an important role in the effects of aerosols on climate, air quality, and local photochemistry. High-precision in-situ measurements of the vertical profiles of these properties are challenging and therefore uncommon. We report here the development of a portable cavity-enhanced albedometer operating at λ = 532 nm for use aboard an unmanned aerial vehicle (UAV). Multi-optical parameters, bscat, babs, extinction coefficient bext, and ω, can be measured simultaneously in the same sample volume. The achieved detection precisions in laboratory were 0.38, 0.21, and 0.43 Mm-1 for bext, bscat, and babs, respectively, for a 1 s data acquisition time. The albedometer was installed on an hexacopter UAV and simultaneous in-situ measurements of the vertical distributions of bext, bscat, babs, and ω were realized for the first time. Here we report a representative vertical profile up to a maximum height of 702 m with a vertical resolution of better than 2 m. The UAV platform and the albedometer demonstrate good performance and will be a valuable and powerful tool for atmospheric boundary layer research.

A unified detection-tracking-estimation vision navigation system and algorithms framework for position and pose estimation of UAV (unmanned aerial vehicle) is proposed in this paper. The major contribution of this work is a novel cooperative object detection algorithm for robust detection of UAV: the spatial color pattern and temporal flicking pattern of the cooperative markers (groups of LEDs) mounted on UAV are adaptively adjusted to make it more salient from background, hence much easier for the vision system to detect it under unconstrained environment, especially during UAV taking-off/landing phase which is typically near ground and suffer more interference from complex scene and changing of illumination. After extracting position and pose information by vision system, particle filtering is used to smooth the trajectory of UAV based on established vehicle dynamics model. Experiment results shows the position and pose measurement based on vision techniques is consistent with IMU measurement and does not show long term drifting error compared to IMU measurement.

The stability of the manipulator is important issue especially in the domain of unmanned aerial vehicle (UAV). Any movements of manipulator greatly affects UAV stability. In particular, the horizontal shift of the center of gravity requires of the UAV the powerful controller, that change forced the propellers of quadrotor to bring the UAV to a stable state. In this paper, we have studied the movements of manipulator and its center of gravity at least horizontally when UAV is in hover mode. As a result, we developed mathematical model and software for calculation of deflection angles between successive links of the manipulator, which provides deviation of the center of mass (COM) of the UAV horizontally less than 1 mm.

Autonomous formation flight has been a fast growing research area during the last decade. Unmanned aerial vehicles (UAVs) can achieve a wide range of benefits from formation flight, such as fuel saving and aerial refueling. In this paper, the development of a small UAV system, called Swallow UAV system, as testbed of formation flight, is presented. Swallow UAV system includes Swallow UAV itself and a Hardware-In-the-Loop Simulation Environment (HILSE). Swallow UAV is a fixed wing, pusher-type, electric motor driven aircraft with 1.4 meter wing span. Its avionics system includes an onboard computer and a sensor system with GPS, IMU, air data sensor, and motor monitoring unit to provide position, velocity, inertial data, and system health. Communications between UAVs and the ground control station (GCS) are conducted by wireless modem. A fuzzy navigation and control system (FNCS) is developed for the waypoint navigation and attitude control of the aircraft. GPS velocity based pseudo attitude and fuzzy logic control are applied to FNCS for attitude estimation and fast implementation of controllers. HILSE is built to verify FNCS with onboard computer on the ground. X-Plane flight simulator is applied to simulate aircraft dynamics and output sensor data. GCS software, built with data distributor, transmits these data to the onboard computer and receive control signal from it so the onboard computer can control the aircraft in X-Plane. HILSE can perform pre-flight test for software debug, which improves safety and efficiency of flight test. The design of Swallow UAV is verified by flight test and the result shows that it has sufficient flight performance with waypoint navigation and attitude control capability to be used as a formation flight testbed.

Modern methods of creating groups of unmanned aerial vehicles (UAVs) require the use of complex (generalised) criteria, introduced mathematical models in the process of optimising the parameters of the UAV components. Such models should simulate the operation of an unmanned aerial vehicle when performing its task. The study considers strategies for diverging dangerously approaching UAVs using areas of dangerous courses and speeds. First, procedures were performed to establish the dangerous course areas of one UAV and the speeds of the second UAV, taking into account their ratio of speeds and dynamics. The areas for the case of UAV with insignificant transients of changes in courses and speeds, the duration of which can be neglected, is provided. In addition, procedures of the establishment of areas of dangerous courses of one UAV and the speeds of the second UAV with significant inertia are considered. Methods of the establishment of areas in the event of a decrease in the speed of the second UAV by active or passive braking are developed. Examples of choosing a safe manoeuvre in a situation of dangerous convergence of two UAVs are given. A more complex situation of approaching two UAVs in the presence of an interfering third UAV is also considered, and a method for choosing a safe manoeuvre is proposed, taking into account the interfering third UAV. Moreover, for such a situation, two alternative procedures for choosing a safe manoeuvre are proposed. The result of solving this problem was a method for establishing the area of dangerous courses and speeds of UAVs, taking into account the inertia-braking characteristics when determining a safe joint divergence manoeuvre taking into account the presence of a third UAV that provides interference.

Aerial manipulation devices have been increasingly tailored to use at the limit of unmanned aerial vehicle (UAV) technology. The utility value of affordable off-the shelf UAVs for aerial manipulation is relatively unexplored as they often do not meet the performance requirements of coupled manipulator design systems. This paper presents the design and validation of a balanced pantograph manipulator prototype for decoupled use, evaluated with bench tests and and flight tests on a quadrotor UAV. The design exhibits two degrees of freedom (DOF) with a larger range of motion than most preceding decoupled manipulators. The paper also discusses an analytical model which maps the centre of gravity (CG) of all the links of the device in its operational range, allowing fine-tuning of a compact counter mass assembly which operates mechanically to achieve a net-zero stability impact on the UAV. This primary function is ideal for close quarters inspection and contact sensing tasks which engage passively with the environment. Results show that the decoupled pantograph manipulator has no measurable stability impact on the UAV, is appropriate for the use cases described and shows promise for development into a coupled design platform.

The article is devoted to the development and research of a kinematic model of stabilization and orientation control of the suspended equipment of an unmanned aerial vehicle (UAV). The created model is based on the kinematic model of a three-axis gimbal (TAG): the structure of the TAG for the UAV, the mathematical description of the TAG of the UAV and the derivation of kinematic equations for the problems of stabilizing and controlling the orientation of the UAV suspension equipment. In the general case, the derivation of the kinematic equations of the TAG on the UAV is a complex process and is similar to the derivation of a kinematic model of a robotic arm with six degrees of freedom. The TAG is considered as a manipulative mechanism with six degrees of freedom: three degrees of freedom are determined by the UAV rotations around the axes of the coordinate system attached to the UAV, and three degrees of freedom are set by the frames of the TAG along the channels of yaw, roll and pitch during rotational movements of these frames around the corresponding axes of the coordinate systems attached to the frames of the TAG. Such a statement in the general case does not have an unambiguous solution for the tasks of stabilization and orientation control of the suspended equipment of UAV. To eliminate this ambiguity, optimization is used in the process of designing the TAG and installing the TAG in such positions on the UAV that reduce the computational complexity of the tasks being solved. The kinematic model is presented in the article by kinematic equations, the solution of which ensures the stabilization of the suspended equipment of UAV, and kinematic equations, the solution of which allows you to control the equipment (camera) of the UAV when tracking moving objects (moving targets) in space. The simulation of the TAG in the MATLAB Simulink software environment was performed. The simulation results in the MATLAB Simulink software environment prove the adequacy of the developed kinematic model of the TAG and its effectiveness for solving the problems of stabilization and orientation control of the suspended equipment of UAV.

The growing popularity of Internet of Things (IoT) with the requirements of highly reliable and low latency has imposed huge challenges to current cellular networks. Using small aerial platforms like unmanned aerial vehicles (UAVs) to assist terrestrial base stations (BSs) is attractive, but it often challenged by the lack of UAV access selection and resource allocation algorithm to balance the network performance and service cost. In this paper, we study the UAV access selection and BS bandwidth allocation problems in a UAV assisted IoT communication network, where a hierarchical game framework is presented. The complicated interactions among UAVs and BSs as well as the cyclic dependency is studied by applying the Stackelberg game theory. Wherein, the access competition among groups of UAVs is formulated as a dynamic evolutionary game and solved by an evolutionary equilibrium. On the other hand, the problem of how much bandwidth should BSs allocate to the UAVs is modeled as a noncooperative game, where the existence and the uniqueness of Nash equilibrium is analyzed. Stochastic geometry tool is used to model the position distribution of network nodes and drive the payoff expressions by taking into account different network parameters. The analytical results for the proposed hierarchical game model and the corresponding solutions are evaluated via simulations, which verify both the validity of our analysis and the effectiveness of the proposed algorithms.

Development and utilization of hexacopter unmanned aerial vehicle platform to characterize vertical distribution of boundary layer ozone in wintertime

The development of unmanned aerial vehicles (UAVs) has become an active area of research in recent years, and very interesting devices have been developed. UAVs are important instruments for numerous applications, such as forest surveillance and fire detection, coastal and economic exclusive zone surveillance, detection of watershed pollution and military missions. The work described in this chapter is part of a larger project, named AIVA, which involves the design and development of an aerial platform, as well as the instrumentation, communications, flight control and artificial vision systems, in order to provide autonomous takeoff, flight mission and landing maneuvers. The focus of the chapter is on one of the main innovative aspects of the project: the onboard wireless distributed data acquisition and control system. Traditionally, UAVs present an architecture consisting of one centralized and complex unit, with one or more CPUs, to which the instrumentation devices are connected by wires. At the same time, they have bulky mechanical connections. In the approach presented here, dubbed “fly-by-wireless”, the traditional monolithic processing unit is replaced by several less complex units (wireless nodes), spread out over the aircraft. In that way, the nodes are placed near the sensors and controlled surfaces, creating a network of nodes with the capacity of data acquisition, processing and actuation. This proposed fly-by-wireless platform provides several advantages over conventional systems, such as higher flexibility and modularity, as well as easier installation procedures, due to the elimination of connecting cables. However, it also introduces several challenges. The wireless network that supports the onboard distributed data acquisition and control system needs to satisfy demanding requirements in terms of quality of service (QoS), such as sustainable throughput, bounded delay and reliable packet delivery. At the same time, it is necessary to guarantee that the power consumption of the battery powered wireless nodes is small, in order to increase the autonomy of the system. Currently there are many different wireless network technologies available in the market. Section 2 presents an overview of the most relevant technologies and discusses their suitability to meet the above requirements. Based on this analysis, we chose the Bluetooth wireless network technology as the basis for the design and development of a prototype of the fly-by-wireless system. The system was implemented using commercial off-the-shelf components, in order to provide a good trade-

Unmanned aerial vehicles (UAVs) play an essential role in emergency cases and adverse environments for applications like disaster detection and mine exploration. To process the massive volume of sensing data generated by various sensory payloads in these applications, existing works either compress deep learning (DL) models to conduct onboard computing, or offload raw data back to the resourceful ground station with the help of relay UAVs due to base station damage. However, the former sacrifices the inference accuracy of DL models (up to 10% accuracy loss), while the latter achieves high accuracy at the cost of significant latency, due to limited wireless communication resources in the multi-hop transmission. To address the problem, exploiting the resources of the UAV swarm including both task UAVs and relay UAVs, we build up an <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</u>ll-<underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</u>ky <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</u>utonomous com<underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</u>uting (ASAP) system to autonomously conduct collaborative computing in the swarm, to achieve both high accuracy and low latency of sensing data processing. In detail, we first propose a novel UAV swarm-native collaborative computing architecture, considering the general hierarchy and clustering structure of UAV swarms, as well as the characteristic of DL model execution. We then design an elastic efficient task scheduler to allocate computing tasks for UAVs, and update the scheduling scheme online when some UAVs are unavailable, with the aid of a lightweight and accurate DL inference performance predictor. Finally, we design an adaptive inter-UAV data compressor, to adapt to the limited and dynamic communication resources between UAVs. Experiment results on 24 airborne computers and five real-world UAVs show that, the proposed system can perform collaborative computing in a timely manner and effectively deal with situations when some UAVs become unavailable.

As a complicated multi-input, multi-output, and time-varying nonlinear system, flight control system of unmanned aerial vehicle (UAV), which determines the whole system’s performance directly, is crucial for the simulation training system design. This chapter mainly focuses on parameter identification of flight control system based on the modeling of UAVs and a specific controller design for the pendulum-like oscillation in micro aerial vehicle (MAV). A predator–prey particle swarm optimization (PSO) algorithm for identifying parameters of UAV flight control system is presented, with the aim of reducing the workload of the designers during the process of designing complicated UAV control system. Besides, a software environment for UAV controller design was developed based on the UAV model and the proposed method. Then a specific kind of controller design involving the pendulum-like oscillation in the hover and stare state for a MAV in the presence of external disturbances is discussed in detail, since the pendulum-like oscillation caused by uncertainty and external disturbances badly jeopardize the performance of hover and stare, resulting in blurred images or even MAV’s overturning. A novel type of PSO-based linear-quadratic regulator (LQR) controller for stabilizing the pendulum-like oscillation is developed, which can enhance the MAV’s performance efficiently.

Quadrotor unmanned aerial vehicles (UAVs) have been actively used in various fields. However, only the altitude and the attitude in three degrees of freedom can be independently controlled since quadrotor UAVs are underactuated systems. A quad tilt rotor UAV solves the problem of an underactuated system in a general quadrotor UAV. The quad tilt rotor UAV can control both position and attitude independently by tilting the directions of the propellers. However, the flight control system in a wide range of attitudes has not been discussed yet, for example a UAV can fly and hover with a 90 pitch angle, and it can even flip over when the thrust direction is tilted in a wide enough range. In this paper, we present the attitude transition flight control system for pitch angles ranging from 0 to 90 since flight conditions with a 90 pitch angle significantly differs from that in a conventional quadrotor UAV flight. We construct an adequate control system for a flight with a wide range of attitude conditions.