Small Quadrotor Unmanned Aerial Vehicle Research Articles

Motor noise reduction of unmanned aerial vehicles

The noise of multi-rotor unmanned aerial vehicles (UAVs) mainly comes from high-speed rotating propellers and brushless direct current motors. With extensive research on the generation mechanism and suppression methods of propeller noise, fruitful results have been achieved on the noise reduction of propellers. Therefore, the noise radiated by UAV motors has received more attention in recent years. In this paper, the noise of the motor of a small quadrotor UAV is reduced by a composite sound-absorbing structure that couples a cylindrical micro-perforated panel absorber (MPPA) with a carbon fiber porous material. The cylindrical MPPA adopts an open design to balance its noise reduction performance and heat dissipation performance. To more realistically reproduce the actual working state of the motor, different shapes of motor loads were designed and manufactured to simulate the propeller. The noise reduction experiment of the UAV motor is carried out in a semi-anechoic chamber. The experimental results show that the composite sound-absorbing structure designed in this paper can effectively reduce the noise of UAV motors and has a good heat dissipation effect. In addition, a custom-made composite sound-absorbing structure was installed on a quad-rotor UAV, and field experiments were carried out. The results of field experiments show that the composite sound-absorbing structure designed in this paper has good practicability to absorb the noise of UAV motors, and this work can provide a reference for the design of silent UAVs in the future.

Integrated Frame Topology Optimization Design of Small Quadrotor UAV

In recent years, the development of UAV (Unmanned Aerial Vehicle) is rapid, but the development of structural design is slow, and the rack designed according to the experience of engineers still has great redundancy. With the rapid development of topology optimization and additive manufacturing, topology optimization design of integrated rack based on additive manufacturing is carried out. In the design process, manufacturing constraints are added and a variety of typical conditions to obtain the final optimization structure are considered. The influence of human empirical factors on the fuselage structure design is reduced scientifically and effectively by using this method. And the lightweight, topological and integrated design of the quadrotor frame is realized.

Effect of Turbulence Modeling Selection Within Helios for Small Quadrotor Aerodynamics

The high-fidelity rotorcraft simulation framework HPCMP CREATE-AV Helios was used to study the impact of turbulence modeling methods on the prediction of a small quadrotor unmanned aerial vehicle. First, the vehicle’s rotor was simulated as an isolated rotor in both hover and forward flight for turbulence model assessment. Predictions using a fully turbulent turbulence model were compared with predictions from several laminar–turbulent transition models. Both comparison with experiments and computational performance were considered. The laminar–turbulent transition models predicted flow separation near the tip for all flight conditions simulated, leading to lower torque and thrust than the fully turbulent model, which predicted attached turbulent flow. The fully turbulent model was shown to provide reasonable comparison with experiments with the lowest computational cost and was used for full vehicle simulations. The full quadrotor configuration calculations were performed in hover and forward flight. The forward flight simulations were performed with and without a detached eddy simulation method, and similar interactional aerodynamics were predicted. The Helios simulation suite is shown to be well-suited for prediction of aerodynamic performance of small-scale rotorcraft.

Soil Moisture Retrieval Model Design with Multispectral and Infrared Images from Unmanned Aerial Vehicles Using Convolutional Neural Network

This paper deals with a soil moisture retrieval model design with airborne measurements for remote monitoring of soil moisture level in large crop fields. A small quadrotor unmanned aerial vehicle (UAV) is considered as a remote sensing platform for high spatial resolutions of airborne images and easy operations. A combination of multispectral and infrared (IR) sensors is applied to overcome the effects of canopies convering the field on the sensor measurements. Convolutional neural network (CNN) is utilized to take the measurement images directly as inputs for the soil moisture retrieval model without loss of information. The procedures to obtain an input image corresponding to a certain soil moisture level measurement point are addressed, and the overall structure of the proposed CNN-based model is suggested with descriptions. Training and testing of the proposed soil moisture retrieval model are conducted to verify and validate its performance and address the effects of input image sizes and errors on input images. The soil moisture level estimation performance decreases when the input image size increases as the ratio of the pixel corresponding to the point to estimate soil moisture level to the total number of pixels in the input image, whereas the input image size should be large enough to include this pixel under the errors in input images. The comparative study shows that the proposed CNN-based algorithm is advantageous on estimation performance by maintaining spatial information of pixels on the input images.

Robust Tuning of Geometric Attitude Controllers for Multirotor Unmanned Aerial Vehicles

In recent years there has been a significant body of literature proposing nonlinear attitude control laws for small-scale multirotor unmanned aerial vehicles (UAVs), motivated by the high maneuverability of these platforms. While tracking trajectories characterized by fast and large attitude changes makes the control problem intrinsically nonlinear, most of the works proposing nonlinear designs is concerned with establishing their stabilizing properties, often deduced by referring to simplified dynamic models, but limited attention has been devoted to performance. As a consequence, less satisfactory results than expected are typically achieved in experiments and the controller gains must be adjusted with trial-and-error procedures to obtain good performance. This paper proposes a model-based tuning method that exploits the cascade structure of the attitude dynamics and that needs only single-axis identified linear models of the angular velocity dynamics to be applied. The tuning of the controller gains is carried out on the linearized closed-loop system with structured synthesis that allows one to enforce robustness against model uncertainty in a systematic way and to achieve a desired level of performance in nominal conditions. The approach is validated by tuning the gains of a novel Proportional/Proportional Integral Derivative (P/PID)-like cascade, which has been developed in the framework of geometric control theory. A thorough analytical comparison of the proposed design with a geometric Proportional Integral (PI)-like controller borrowed from the literature is complemented with experiments conducted on a small quadrotor UAV.

The Methods of Information Acquisition and Information Fusion of the Photoelectric Sensor-Based Quadrotor Unmanned Aerial Vehicle

When quadrotor unmanned aerial vehicle (UAV) is performing various tasks, even a small angular error will affect the evaluation of the entire motion trajectory. The multiple photoelectric sensor information fusion technology and the ARM microprocessor platform are used to form an attitude reference system for UAV. First, the hardware design of the small quadrotor UAV attitude reference system based on an ARM is introduced. The design framework and information acquisition module are expounded. In terms of the software of the system, the photoelectric sensor is used to receive different kinds of information, and the dynamic loading component is adopted as the solution to the interface diversification problems. Based on the attitude reference system, the collected information needs to be fused. The Kalman filtering is taken as the research object. Combined with the multiple photoelectric sensor information fusion technology, the Kalman filtering method is improved in the data preprocessing, and the low-pass filtering is added. Therefore, the abnormal data is filtered, and the estimated values are converged in a short time. Then, the data fusion is performed by the joint Kalman filter, least-squares fusion, and extended Kalman filter, respectively. During the experimental process, the system is proved to have good robustness, that is, in the case of individual sensor failure, the attitude acquisition section still obtains accurate attitude information of the UAV. The attitude reference system of UAV is realized. With the help of multi-sensor/information fusion technology, the attitude of the UAV is better handled, and its flight stability is improved.

가우시안 프로세스 모델 기반 강화 학습

Reinforcement learning (RL) has been a promising approach in robotics and control because data-driven learning methods can reduce system reliance on human engineering knowledge. A model-based RL autonomously learns observed dynamics based on a general flexible nonparametric approach. Probabilistic Inference for Learning COntrol (PILCO) is one of the most data-efficient model-based RL frameworks. Since PILCO sets up a Bayesian estimator problem with a Gaussian process regression, it derives a fully deterministic approximate inference for policy evaluation, which makes it computationally efficient. However, PILCO requires a task-specific scenario. If an agent is given a new goal that is different than the original training goal, PILCO should relearn its model from scratch. This paper extends PILCO to tune a linear feedback controller with a quadratic cost function, where the quadratic cost function commonly used in control systems can adjust the trade-off relationship between control input consumption and convergence rate. The suggested method is not only able to maintain the analytic and deterministic approximate inference for policy evaluation, but is also able to interpret the controller design. The suggested RL framework is applied to the control of a small quadrotor unmanned aerial vehicle (UAV) with no given dynamics. The simulation results show the convergence of the learning control performance as a function of the number of RL iterations.

A UAV software flight management system using arinc communication protocols

Most large commercial aircraft use a flight management system (FMS) to provide aircraft state estimation, trajectory prediction, lateral and vertical guidance, flight plans, and target setpoints (e.g., optimal cruise speed), among other functionality [1]. With unmanned aerial vehicles (UAVs) gaining popularity in commercial and military applications [2], the integration of UAVs in shared airspace with current aircraft has become an important problem to address. There has been consideration for the use of unmanned aircraft for package delivery with the use of small quadrotor UAVs for local demand [3] and large unmanned commercial aircraft for shipping goods internationally [4]. With the UAV industry poised to grow [2], one must consider how to integrate UAVs with the current systems for manned aircraft. Due to the importance of FMS to aircraft, a logical step would be to consider an FMS for UAVs that can adhere to current aircraft regulations and protocols. Flight management systems for UAVs can involve certification, collision detection, mission planning, and many other topics. One can find a number of simulated FMS for consumer flight simulators (i.e., Microsoft Flight Simulator and X-Plane [6]) that try to replicate the interface and functionality of currently available flight management systems. The purpose of this article is to take this idea further by building an FMS in software that can interface with real aircraft and UAVs using industry standard communication protocols.

Pitching Moment Caused by Rotor Flow Interference on a Small Quad-rotor Unmanned Aerial Vehicle in a Uniform Flow

Pitching Moment Caused by Rotor Flow Interference on a Small Quad-rotor Unmanned Aerial Vehicle in a Uniform Flow

Reduction of the head-up pitching moment of small quad-rotor unmanned aerial vehicles in uniform flow

Multi-rotor unmanned aerial vehicles are unstable in headwind because of nose-up pitching moment generation and thrust degradation. Reducing the pitching moment generation could enhance the tolerance of the unmanned aerial vehicles to wind and improve cruise flight speed. In this study, a canted rotor configuration was proposed to reduce the moment in uniform flow and examined. The objective of the study is to evaluate the effect of moment reduction by canted rotors. First, flow interactions between rotors of the quad-rotor were visualized using a smoke wire method. Second, the moment reduction by canted rotors was estimated based on isolated rotor performance. Third, the moment of the quad-rotor varying the body pitching angle was examined using a wind tunnel. At an 8 m/s wind, when the body pitching angle is horizontal, slanting the rotor by 20° to outside the body degraded the moment by 26% compared with the parallel rotor configuration.

Position and attitude tracking control for a quadrotor UAV

A synthesis control method is proposed to perform the position and attitude tracking control of the dynamical model of a small quadrotor unmanned aerial vehicle (UAV), where the dynamical model is underactuated, highly-coupled and nonlinear. Firstly, the dynamical model is divided into a fully actuated subsystem and an underactuated subsystem. Secondly, a controller of the fully actuated subsystem is designed through a novel robust terminal sliding mode control (TSMC) algorithm, which is utilized to guarantee all state variables converge to their desired values in short time, the convergence time is so small that the state variables are acted as time invariants in the underactuated subsystem, and, a controller of the underactuated subsystem is designed via sliding mode control (SMC), in addition, the stabilities of the subsystems are demonstrated by Lyapunov theory, respectively. Lastly, in order to demonstrate the robustness of the proposed control method, the aerodynamic forces and moments and air drag taken as external disturbances are taken into account, the obtained simulation results show that the synthesis control method has good performance in terms of position and attitude tracking when faced with external disturbances.