Testing Unmanned Aerial Vehicle Missions in a Scaled Environment

UAV research generally follows a path from computer simulation and lab tests of individual components to full integrated testing in the field. Since realistic environments are difficult to simulate, its hard to predict how control algorithms will react to real world conditions such as varied lighting, weather, and obstacles like trees and wires. This paper introduces a methodic approach to developing UAV missions. A scaled down urban environment provides a facility to perform testing and evaluation (T&E) on control algorithms before flight. A UAV platform and test site allow the tuned control algorithms to be verified and validated (V&V) in real world flights. The resulting design methodology reduces risk in the development of UAV missions.     

Development of Unmanned Aerial Vehicle (UAV) system with waypoint tracking and vision-based reconnaissance

This paper introduces the developed UAV system for low cost operation and an EOS (Electro Optical System) laboratory. This paper highlights an autonomous navigation system based on microcontrollers that can track a target using images, take three-dimensional measurements of the target, and acquire high quality images. The hardware system and an algorithm for the EOS verify the performance of the image tracking system and 3-D measurement of the target’s position. 3-D position estimations for the target are solved using the mathematical relationship between the UAV and target. Although an on-board EOS can make errors in 3-D measurement, the proposed approach shows improved accuracy and confidence for 3-D target tracking using a postprocessing method.     

Object Tracking-Based “Follow-Me” Unmanned Aerial Vehicle (UAV) System

The applications of information technology (IT) tools and techniques have, over the years, simplified complex problem solving procedures. But the power of automation is inhibited by the technicality in manning advanced equipment. To this end, tools deliberately combating this inhibition and advancing technological growth are the Unmanned Aerial Vehicles (UAVs). UAVs are rapidly taking over major industries such as logistics, security, and cinematography. Among others, this is a very efficient way of carrying out missions unconventional to humans. An application area of this technology is the local film industry which is not producing quality movies primarily due to the lack of technical know-how in utilizing these systems. This study therefore aim to devise an autonomous object tracking UAV system that would eliminate the complex procedure involved in stabilizing an aerial camera (aerial bot) midair and promote the creation of quality aerial video shooting. The study adopted Unified Modeling Language (UML) tools in modeling the system’s functionality. The traditional Server-Client model architecture was adopted. The OpenCV library employed proved highly efficient in aiding the tracking procedure. The system provided a usable web controller which provides easy interaction between the pilot and the drone. Conclusively, investments in UAVs would enhance creation of quality graphic contents.     

Unmanned Aerial Vehicle Security Using Recursive Parameter Estimation

The proliferation of Unmanned Aerial Vehicles (UAVs) brings about many new security concerns. A common concern with UAV security is for an intruder to take control of a UAV, which leads for a need for a real time anomaly detection system. This research resulted in a prototype UAV monitoring system that captures flight data, and then performs real time estimation and tracking of the airframe and controller parameters. The aforementioned is done by utilizing the Recursive Least Squares Method (RLSM). Using statistical validation and trend analysis, parameter estimates are critical for the detection of cyber attacks and incipient hardware failures that can invariably jeopardize mission success. The results demonstrate that achieving efficient anomaly detection during flight is possible through the application of statistical methods to profile system behavior. The anomaly detection system that was designed can be performed in real time while the UAV is in flight, constantly verifying its parameters.     

无人机在我国内河航道巡航的可操作性分析

目前,无人机凭借可靠、灵活、方便、高效的优势,可作为内河航道管理的一种安全有效的空中监管方式。笔者首先分析了无人机在我国内河航道巡航工作的现状,并对几种常见的无人机展开叙述,系统分析了无人机的组成及其动力系统、控制系统等相关系统,阐明了无人机在内河航道巡航应用的可行性。     

高空无人机联合通信故障诊断模型仿真

高空多飞机的联合通信系统的安全性,关系到空中安全.由于双机、多机的高空联合通信过程都以地面服务器为基础,通信系统采用多区域、多服务器联合工作的模式,通信设备以节点的形式,被人为分成若干个固定数据块储存区,对不同的无人机来说,所属的不同区域的故障特征表达方式不同.传统的故障数据检测方法进行无人机通信故障检测时,很难对地空区域进行准确的故障区域划分,也没有考虑不同区域不同故障特征的表达,故障反推对应过程容易出现混乱,导致故障检测的准确率降低.提出一种基于神经网络算法的云计算环境下高空双机通信中的单方故障挖掘方法.对数据储存节点进行分类,利用神经网络建立故障数据子数据块节点挖掘模型,从而完成了故障数据的挖掘.实验结果表明,利用改进算法进行云计算环境下高空双机通信中的单方故障挖掘,能够有效提高挖掘的准确率和挖掘效率.     

无人机快速逃逸过程中障碍物自动识别仿真

在无人机快速逃逸过程中,为了保证逃逸成功,需要对追击者设置的突变障碍物进行准确的视觉识别.由于障碍物对无人机丽言,在出现的位置与出现的形式上,存在很强的突变性,传统的立体视觉模式识别方法中,障碍物在机器视觉需要建立高纬度模型表示障碍物的突变性和非线性,导致识别过程中的立体视差存在较大偏差,无法快速、准确识别出障碍物信息.提出了非参数核密度的无人机快速逃逸过程中障碍物自动识别模型,应用高斯核密度估计进行背景建模,对视频序列中的像素点进行概率密度分析,利用对像素点阈值进行设置,采集障碍物目标,采用连续视频序列中的多帧差分法,构建背景的自适应更新模型,克服光照、抖动等因素对障碍物目标背景重建的影响,实现无人机快速逃逸过程中障碍物自动识别.实验结果说明,采用所提方法可获取准确的障碍物自动识别效果.     

高空长航时无人机系统的总体方案评价准则研究

在对有人驾驶飞机作战效能评估方法的分析研究基础上,建立了高空长航时无人机总体方案的一般评价准则及具体的数学评估公式;详细分析了影响高空长航时无人机侦察效能的总体性能参数,并在此基础上建立了侦察效能的评估公式;分析了当高空长航时无人机具备攻击能力时,影响其攻击效能的参数,在此基础上建立了攻击效能的评估公式;并运用该方法对“全球鹰”和“捕食者”两种长航时无人机的效能指数进行了定量评估,验证了该评估准则的可用性。     

基于巡逻无人机的轻量型安全帽佩戴检测方法与应用

目前,安全帽检测系统主要使用固定摄像头,无法实现全区域检测,而基于深度学习的检测算法结构复杂、计算成本高,无法满足移动端和嵌入式设备的部署要求。针对上述问题,该文提出一种基于无人机的安全帽轻量型视觉检测算法。系统通过无人机平台搭载的相机对施工现场进行图像采集,并无线传输至后台计算机进行处理,检测算法基于 YOLOv5s 框架进行了轻量化改进。针对无人机采集影像中目标占比较小的问题,该文采用了多尺度检测、图像预处理、正负样本不均衡等方法,对 YOLOv5s 目标检测算法进行针对性改进。测试结果表明,与原模型相比,轻量型目标检测模型的平均精度均值仅下降了 1.72%,但在同一 CPU 上的推理速度提升了 1 倍,浮点计算量由原来的每秒 165 亿次压缩至每秒 34 亿次,模型大小约为原模型的 1/10。     

Integral Backstepping Control of an Unconventional Dual-Fan Unmanned Aerial Vehicle

In this paper, a dynamic model of vertical take-off and landing (VTOL) aerial vehicles, having lateral and longitudinal rotor tilting mechanism, is first developed using a Newton–Euler formulation. Then an integral backstepping (IB) control technique is proposed to improve the pitch, yaw, and roll stability of the vehicle. Such control mechanisms enables the UAV to perform complex tasks that no other Unmanned Aerial Vehicles (UAVs) can execute such as hover pitched. This control tactic allows the vehicle under investigation, eVader, to use the full potential of its flying characteristics enabled by the novel dual-axis oblique active tilting (OAT) mechanism, which enables it to maneuver inside obstructed environments. The potential of the eVader as a small UAV and its model are verified and then used to for autonomous take-off and landing as well as stabilizing the vehicle’s attitude. Finally, diverse simulation scenarios on attitude and position control, stabilization and autonomous take off and landing are presented.     

A Practical Visual Servo Control for an Unmanned Aerial Vehicle

An image-based visual servo control is presented for an unmanned aerial vehicle (UAV) capable of stationary or quasi-stationary flight with the camera mounted onboard the vehicle. The target considered consists of a finite set of stationary and disjoint points lying in a plane. Control of the position and orientation dynamics is decoupled using a visual error based on spherical centroid data, along with estimations of the linear velocity and the gravitational inertial direction extracted from image features and an embedded inertial measurement unit. The visual error used compensates for poor conditioning of the image Jacobian matrix by introducing a nonhomogeneous gain term adapted to the visual sensitivity of the error measurements. A nonlinear controller, that ensures exponential convergence of the system considered, is derived for the full dynamics of the system using control Lyapunov function design techniques. Experimental results on a quadrotor UAV, developed by the French Atomic Energy Commission, demonstrate the robustness and performance of the proposed control strategy.     

具有JTIDS接口的无人机仿真系统

建立了一个具有联合战术信息分发系统接口的无人机仿真系统.在该系统中建立了某型无人机的动力学仿真模型,其气动系数均通过风洞试验获得,并采用单纯形调优法求取无人机初始状态;设计了控制无人机姿态和控制飞行轨迹的内外环控制系统模型;根据联合战术信息分发系统特性,采用模块化方法建立了联合战术信息分发系统接口,使操作员能通过仿真数据链对无人机动力学模型进行任务控制和状态监视.最后进行了虚拟任务仿真试验,结果表明该系统可以满足一定的战术任务需求.     

Image Based and Hybrid Visual Servo Control of an Unmanned Aerial Vehicle

The use of unmanned aerial vehicles (UAVs) for military, scientific, and civilian sectors are increasing drastically in recent years. This study presents algorithms for the visual-servo control of an UAV, in which a quadrotor helicopter has been stabilized with visual information through the control loop. Unlike previous study that use pose estimation approach which is time consuming and subject to various errors, the visual-servo control is more reliable and fast. The method requires a camera on-board the vehicle, which is already available on various UAV systems. The UAV with a camera behaves like an eye-in-hand visual servoing system. In this study the controller was designed by using two different approaches; image based visual servo control method and hybrid visual servo control method. Various simulations are developed on Matlab, in which the quadrotor aerial vehicle has been visual-servo controlled. In order to show the effectiveness of the algorithms, experiments were performed on a model quadrotor UAV, which suggest successful performance.     

无人机吊挂飞行系统的减摆控制设计

主要考虑了四旋翼无人机（Unmanned aerial vehicle,UAV）吊挂飞行系统的位置控制及负载摆动抑制的设计问题.在存在欠驱动特性以及未知系统参数的约束下,本文基于能量法设计了一种非线性控制策略,实现了对无人机位置的精确控制和飞行过程中负载摆动的快速抑制.基于Lyapunov方法的稳定性分析证明了闭环系统的稳定性,位置误差的收敛及摆动的抑制.实验结果表明本文提出的控制策略取得了较好的控制效果.     

某型无人机机载遥测系统帧结构设计

本文根据某型无人机遥测系统的特点与需求,结合现代遥测系统的典型应用,对传统固定格式的PCM帧结构进行了改进,设计了一种可支持每组多路多组并发采集的PCM码流与多路异步数据码流复用传输方式的帧结构.     

基于运行时验证的无人飞行系统安全威胁检测方法

无人飞行系统（Unmanned Aerial Systems,UAS）的软、硬件存在缺陷以及遇到外部恶意攻击,会给UAS的安全性带来极大威胁.由于UAS的运行环境复杂多变,很多因素在开发过程中难以准确预测,因此研究有效的运行时安全保证机制具有重要意义.本文提出一种基于运行时验证的UAS安全威胁检测方法.首先对UAS可能遇到的多种安全威胁进行分析并采用离散时间时序逻辑进行描述,提出相应的UAS-DL语言描述安全监控规约;然后基于交错自动机提出了自动生成安全威胁监控器的算法,并利用参数化方法实现对多UAS的安全监控.为了提高检测的准确性,进一步研究了将运行时验证和贝叶斯网络推断结合的方法.采用实际的UAS开发仿真平台Ardupilot进行了实验,并设计了将监控器独立部署在FPGA硬件上的方法,避免对UAS计算资源的过多占用.实验结果表明上述方法能够有效检测UAS的安全威胁.