基于地面站辅助的无人机自主架线系统

将无人机（unmanned aerial vehicle, UAV）技术用于实现电力线展放正逐步成为电力行业发展的主要趋势,研究无人机自主架线技术能够有效提高作业效率、降低施工成本和保障工人安全。但现阶段无人机架线技术面临的问题主要有：1）大多数无人机依赖人工操控或地面站发布航点控制,智能化水平低,长期作业会给电力工人带来较强负荷;2）无人机缺乏自主避障能力且感知能力不足,电线、电杆等障碍物会对其造成安全隐患。为解决上述问题,首先,构建了无人机自主架线系统的硬件框架和以ROS（robot operating system,机器人操作系统）为基础的模块化软件框架,并在此基础上实现了架线任务规划算法和架线弓检测算法等,使无人机具备稳定的自主架线能力。然后,利用碰撞检测方法构建了无人机碰撞模型,并提出了无人机路径规划算法,同时引入地面站辅助避障策略,以有效提高无人机的安全性。实验结果表明：所设计的无人机自主架线系统的软、硬件框架合理,架线任务规划算法能帮助无人机高效稳定地完成自主架线任务;地面站能够实时监控无人机状态,并在必要时及时辅助无人机避障,最大程度地保证了无人机的安全。所设计系统安全可靠,可满足实际电力架线作业的需求。     

Power Optimized Multiple-UAV Error-Free Network in Cognitive Environment

Many extensive UAV communication networks have used UAV cooperative control. Wireless networking services can be offered using unmanned aerial vehicles (UAVs) as aerial base stations. Not only is coverage maximization, but also better connectivity, a fundamental design challenge that must be solved. The number of applications for unmanned aerial vehicles (UAVs) operating in unlicensed bands is fast expanding as the Internet of Things (IoT) develops. Those bands, however, have become overcrowded as the number of systems that use them grows. Cognitive Radio (CR) and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks, and hence as technological solutions for future generations, from this perspective. As a result, combining CR with UAVs has the potential to give significant benefits for large-scale UAV deployment. The paper examines existing research on the subject of UAV covering and proposes a multi-UAV cognitive-based error-free model for energy-efficient communication. Coverage maximization, power control, and enhanced connection quality are the three steps of the proposed model. To satisfy the desired signal-to-noise ratio, the covering zone efficacy is investigated as a function of the distance among UAVs stationed in a specific geographic region depending on multiple deployment configurations like as rural, suburban, and urban macro deployment scenarios of the ITU-R M.2135 standard (SNR).     

Optimum design of three-dimensional behavioural decentralized controller for UAV formation flight

This article proposes a behavioural decentralized approach that allows an unmanned aerial vehicle (UAV) formation flight to carry out a waypoint-passing mission effectively. The objective of the proposed controller is to make each UAV in the formation fly through predefined waypoints while maintaining its distance from other UAVs. To perform these two tasks, which can conflict with each other, coupled dynamics of UAVs is considered; this combines the dynamics of all the members in the formation. To apply the behavioural decentralized controller on the basis of the coupled dynamics, a feedback linearization technique with a diffeomorphic transfer map is derived for a three-dimensional UAV kinematics model. A behavioural approach in which the control input is decided by the relative weight of each UAV's desired behaviour is considered, so that the UAVs can react promptly in various situations. Optimization techniques of the gain matrices are also performed to improve the performance of the formation flight using eigen-structure analysis and Cholesky decomposition. To verify the performance of the proposed controller, numerical simulation is performed for a waypoint-passing mission of multiple UAVs.     

无人机被动音频探测和识别技术研究

为解决近场空域低、慢、小旋翼无人机的安全威胁,提出基于音频信号分析的无人机探测识别方法。该方法采用改进流程和参数的梅尔频率倒谱系数(Mel-Frequency Cepstral Coeffi-cients,MFCC)和其一阶差分作为无人机音频的特征参数,结合提出的多距离分段采集法,通过训练高斯混合模型(Gaussian Mixture Model,GMM),建立多特征的无人机音频"指纹库",最后用特征匹配算法实现无人机的探测和识别。实验结果表明,所提出的方法在典型郊区环境中可实现150 m距离内无人机的探测和识别,识别率达到84.4%。     

多体组合式无人机飞行力学稳定性分析及增稳控制研究

多体组合式无人机是一种新概念飞行器,由多个小型无人机以翼尖铰接连接组成,该概念飞行器能够融合小型无人机与高空长航时无人机两类飞行平台的性能和任务优势,发展潜力巨大。基于Newton-Euler方程及升力线方法建立多体组合式无人机飞行力学模型,针对允许相对滚转运动自由度的双机组合式无人机系统进行配平及稳定性分析。结果表明,不同于传统构型飞行器,多体组合式无人机系统具有不稳定复合运动飞行模态,该复合模态由相对滚转运动主导,在无控状态下该构型飞行器无法稳定飞行。在完成动力学建模的基础上,基于PID控制方法,为每个单体飞行器单独设计增稳控制回路以达到增稳控制目的,仿真结果表明该控制思路有效,可以快速镇定发散的飞行力学系统。     

Trajectory optimization for unmanned aerial vehicle formation reconfiguration

The results of trajectory optimization to reconfigure unmanned aerial vehicle (UAV) formation in the event of a critical failure are presented. The formation reconfiguration process includes two distinct manoeuvres: an escape manoeuvre for a malfunctioning UAV and a replacement movement for an alternative UAV related to its position. This article deals with both manoeuvres but focuses more on the replacement movement. The trajectory optimization problem of the escape manoeuvre is formulated as a minimum-time problem to reduce the possibility of collisions resulting from a failure, whereas the problem of the replacement movement is formulated as a final-time fixed minimum-fuel problem to secure the durability of the group of UAVs. These problems are solved by means of sequential quadratic programming. To evaluate the performance of the optimization results, fuel consumption for the replacement movement is considered and optimization of a three-phase reference trajectory is performed. The results show that the trajectory optimization reduces the fuel consumption and saves time.     

An SoPC-based object tracking quadrotor

In this paper, a quadrotor unmanned aerial vehicle (UAV) is designed and implemented, and the whole control system is realized on an SoPC platform. The dynamic mathematical model of a quadrotor is derived using Euler–Lagrange equations. A simulation is conducted by applying PID controllers to control the derived model to verify that the PID method is able to stabilize a quadrotor. The aircraft is stabilized according to the sensory data from a tri-axis gyroscope and a tri-axis accelerometer providing angular rates and Euler angles, respectively, for the control system. In addition, a CMOS camera and an ultrasonic sensor mounted on the bottom of the aircraft enable the aircraft with functions of detecting and tracking a moving object, while the aircraft is flying. The resulting system can stably fly in indoor environments and track a specific object, satisfying the design and implementation purpose.     

蜂群无人机编队内无线紫外光协作避让算法

在战场复杂电磁环境下,保证蜂群无人机编队机间飞行安全和编队内可靠通信尤为重要。本文提出一种蜂群无人机编队内无线紫外光协作避让算法,结合无线紫外光覆盖特点设计紫外虚拟围栏避让策略,基于增强矢量场直方图法针对无人机在避让时的运动状态的代价函数进行改进,采用无迹卡尔曼预测器预测邻近无人机的飞行状态。在两种预测场景下的避让仿真中,结果表明,与增强矢量场直方图法进行对比,本文算法的整体运动轨迹平滑,局部避让时无明显抖动,避让路径总长度平均减少3.46%,总耗时平均减小18.94%,验证了蜂群无人机编队内无线紫外光协作避让算法的有效性。     

Grasp Planning and Visual Servoing for an Outdoors Aerial Dual Manipulator

This paper describes a system for grasping known objects with unmanned aerial vehicles (UAVs) provided with dual manipulators using an RGB-D camera. Aerial manipulation remains a very challenging task. This paper covers three principal aspects for this task: object detection and pose estimation, grasp planning, and in-flight grasp execution. First, an artificial neural network (ANN) is used to obtain clues regarding the object’s position. Next, an alignment algorithm is used to obtain the object’s six-dimensional (6D) pose, which is filtered with an extended Kalman filter. A three-dimensional (3D) model of the object is then used to estimate an arranged list of good grasps for the aerial manipulator. The results from the detection algorithm—that is, the object’s pose—are used to update the trajectories of the arms toward the object. If the target poses are not reachable due to the UAV’s oscillations, the algorithm switches to the next feasible grasp. This paper introduces the overall methodology, and provides the experimental results of both simulation and real experiments for each module, in addition to a video showing the results.     

Bio-inspired wing morphing for unmanned aerial vehicles using intelligent materials

Biologically inspired engineering or Biomimicry is the practice of developing designs and technologies inspired by nature. This conscious use of examples from nature is a form of applied case-based reasoning thus treating nature itself as a database of solutions that have survived for millions of years-survival of the fittest. Inspired by nature, we have developed aircraft wings that imitate the amazing flight of birds. This bio-inspired effort, which is the result of a collaborative research program with Defence Science Organisation National Laboratories of Singapore, is concerned with the design and development of a novel wing prototype for unmanned aerial vehicles (UAVs) that morphs seamlessly without the use of complex hydraulics and/or servo motors. The novel design, selected from a number of designs, is characterised by a high degree of flight adaptability, enhanced manoeuvrability and improved performance with a limited added weight. These characteristics were attained through the use of shape memory alloys as actuators in an antagonistic fashion. Unlike compliant actuators that require continued input of thermal energy, antagonistic setup does not suffer from this difficulty. This is because they require the thermal energy to deform the wing but not to maintain its morphed shape. Structural analysis based upon safety factors specified by FAR23 standards and aerodynamic analysis using FLUENT were conducted on the novel designs to validate their suitability as viable wings for UAVs. In addition, conditioning of the shape memory actuators was conducted using a specially designed circuitry that imposes the appropriate heating and cooling cycles at set periodic times. The outcome of this study is manifest in the new designs that satisfy the missions of different UAVs.     

支持无人机遥感影像的场景多树组织与跨源调度技术

针对无人机(UAV)影像等多源影像构建全球虚拟场景的数据组织和调度问题,研究了无人机影像的预处理方法,讨论了适于可视化需要的球体简化投影方法以及全球虚拟场景的结构,并在此基础上提出了支持无人机影像的全球场景多线性四叉树的组织方式,介绍了无人机影像等多源影像跨源影像衔接与调度的关键技术.用5.12汶川大地震中获取的无人机影像数据进行的实验证明,采用文中提出的数据处理与组织管理方法,能够减少数据存储的冗余性,提高系统运行的效率,方便数据的管理与更新,高效地提供灾情信息可视化服务.     

Quaternions Complementary Filter for Attitude Algorithm Research

Quaternions complementary filter attitude algorithm was conducted on the unmanned aerial vehicle( UAV) platform. This introduces traditional attitude algorithm and attitude quaternion complementary filter algorithm difference,and the attitude quaternion complementary filter algorithm realization are introduced in details.     

Gull-inspired joint-driven wing morphing allows adaptive longitudinal flight control

Birds dynamically adapt to disparate flight behaviours and unpredictable environments by actively manipulating their skeletal joints to change their wing shape. This in-flight adaptability has inspired many unmanned aerial vehicle (UAV) wings, which predominately morph within a single geometric plane. By contrast, avian joint-driven wing morphing produces a diverse set of non-planar wing shapes. Here, we investigated if joint-driven wing morphing is desirable for UAVs by quantifying the longitudinal aerodynamic characteristics of gull-inspired wing-body configurations. We used a numerical lifting-line algorithm (MachUpX) to determine the aerodynamic loads across the range of motion of the elbow and wrist, which was validated with wind tunnel tests using three-dimensional printed wing-body models. We found that joint-driven wing morphing effectively controls lift, pitching moment and static margin, but other mechanisms are required to trim. Within the range of wing extension capability, specific paths of joint motion (trajectories) permit distinct longitudinal flight control strategies. We identified two unique trajectories that decoupled stability from lift and pitching moment generation. Further, extension along the trajectory inherent to the musculoskeletal linkage system produced the largest changes to the investigated aerodynamic properties. Collectively, our results show that gull-inspired joint-driven wing morphing allows adaptive longitudinal flight control and could promote multifunctional UAV designs.     

Obstacle detection and avoidance with noisy measurements using danger zone concepts

Potential collision danger increases if a vehicle gradually moves closer to other vehicles or obstacles. If the collision time can be predicted before the vehicle is dangerously close to other vehicles or obstacles, the vehicle can devise an effective evasive maneuver or reroute its path, thus avoiding collision. This paper proposes an obstacle avoidance algorithm for unmanned vehicles in an unknown environment. The proposed avoidance algorithm uses the danger zone concept to determine whether the obstacle or surrounding vehicle will cause a possible collision. The danger zone is constructed around the vehicle by using semi-algebraic functions. The possible collision can be predicted by checking the sign of these semi-algebraic functions. The semi-algebraic functions for constructing the danger zone apply the relative velocities between the vehicle, and other vehicles or obstacles and can be used for both two- and three-dimensional cases. Several avoidance schemes are provided, with examples to demonstrate the concept of the proposed approach.     

Complete morphing wing design using flexible-rib system

This study is concerned with the complete design, analysis, functional prototyping and flight testing of a novel morphing wing system for use in a relatively small (<10 kg) unmanned aerial vehicles (UAVs). To achieve improved flight performance with limited weight penalty, camber-adjustable morphing wing was designed using flexible servomotor-actuated mechanisms. The current design, which was originally conceptualized by Monner et al. (Smart structures and materials: industrial and commercial applications of smart structures technologies. Proceedings of SPIE 3326, pp 60–70, 1998), ensures that the airfoil shape of the wing is able to continuously morph between the non-cambered and the cambered configurations. The morphing function of the wing is achieved using a flexible-rib system driven by onboard servomotor-rocker. This unique design of a flexible-rib assembly enables the airfoil of the wing to be accurately morphed to the target configuration. With the aid of aerodynamic and finite element analyses, the flexible rib assembly performance and structural integrity are evaluated and assessed. The design process was in compliance with aircraft design standards, including the Federal Aviation Regulations—Part 23. The functional prototype of the flexible rib morphing-wing enabled UAV was manufactured and assembled and a test plane was ground tested. The success of the entire project, including flight testing of the flexible rib assembly is summarized in this paper.     

Efficient unmanned aerial vehicle formation rendezvous trajectory planning using Dubins path and sequential convex programming

Trajectory planning of formation rendezvous of multiple unmanned aerial vehicles (UAVs) is formulated as a mixed-integer optimal control problem, and an efficient hierarchical planning approach based on the Dubins path and sequential convex programming is proposed. The proposed method includes the assignment of rendezvous points (high level) and generation of cooperative trajectories (low level). At the high level, the assignment of rendezvous points to UAVs is optimized to minimize the total length of Dubins-path-based approximate trajectories. The assignment results determine the geometric relations between the UAVs’ goals, which are used as equality constraints for generating trajectories. At the low level, trajectory generation is treated as a non-convex optimal control problem, which is transformed to a non-convex parameter optimization and then solved via sequentially performing convex optimization. Numerical experiments demonstrate that the proposed method can generate feasible trajectories and can outperform a typical nonlinear programming method in terms of efficiency.     

统计过程控制在无人机故障预报系统中的应用

无人机故障预报是无人机故障检测的重要组成部分之一,它能有效地减小无人机的故障发生率。利用统计过程控制(SPC)理论,从数理统计的角度对某无人机的测试数据进行分析,并根据常见的五种故障数据,设计了一套无人机故障预报系统,同时给出了系统的工作原理和具体的实现过程。本系统有助于技术人员发现无人机的潜在故障并判断检测设备是否虚警,具有良好的使用性能和价值。     

基于传染-免疫机制的无人机集群协同探测与跟踪

目标跟踪是无人机集群作战中的一个重要问题.为使无人机集群在进行目标跟踪的过程中快速做出响应,提出一种基于传染-免疫仿生模型的无人机集群协同探测及跟踪策略.通过对传染机制和免疫机制的生物机理进行分析,建立基于传染-免疫机制的仿生模型,该模型包括直接传染、交叉传染和免疫修复3个子过程,将其映射到无人机集群目标跟踪中,实现数...     

一种基于小型无人机的风场测量方法

利用无人机携带皮托一静压管及有关仪器测风是一种有价值的风场测量技术,其成本低、机动灵活、可大区域连续探测,在军事和民用领域都具有十分广阔的应用前景.针对无人机气象探测系统的特点,提出了一种工程上实用的无人机测风方法,分析了主要的误差源,包括静压位置误差、偏航角误差和风场数据处理方法,并给出了相应的补偿和解决措施.试验和试用结果都表明,测风子系统能连续实时获取风场参数,测量精度高,性能稳定可靠.     

The Identification of the Wind Parameters Based on the Interactive Multi-Models

The wind as a natural phenomenon would cause the derivation of the pesticide drops during the operation of agricultural unmanned aerial vehicles (UAV). In particular, the changeable wind makes it difficult for the precision agriculture. For accurate spraying of pesticide, it is necessary to estimate the real-time wind parameters to provide the correction reference for the UAV path. Most estimation algorithms are model based, and as such, serious errors can arise when the models fail to properly fit the physical wind motions. To address this problem, a robust estimation model is proposed in this paper. Considering the diversity of the wind, three elemental time-related Markov models with carefully designed parameter α are adopted in the interacting multiple model (IMM) algorithm, to accomplish the estimation of the wind parameters. Furthermore, the estimation accuracy is dependent as well on the filtering technique. In that regard, the sparse grid quadrature Kalman filter (SGQKF) is employed to comprise the computation load and high filtering accuracy. Finally, the proposed algorithm is ran using simulation tests which results demonstrate its effectiveness and superiority in tracking the wind change.