基于红外视觉/激光雷达融合的目标识别与定位方法

近年来,基于可见光图像的目标识别在无人车感知领域得到了广泛应用.然而,可见光图像目标识别无法应用于弱光和黑暗环境.针对于此,提出了一种基于红外视觉/激光雷达融合的目标识别与定位算法.首先,通过基于颜色迁移的数据增强训练方法,提高了红外目标识别算法的泛化性能.继而,提出了一种基于激光雷达修正的单目深度估计方法,通过视觉图...     

基于改进DeepSORT的视觉/激光雷达目标跟踪与定位方法CSCD

通过结合目标跟踪与相对定位,在对多帧检测目标进行关联与分析的同时,可以获取其三维信息。但当目标外观特征变换较大时,传统目标跟踪算法较易发生漏匹配或身份变换,而仅依靠对齐点云的相对定位算法较易出现定位失效的情况。针对以上问题,提出了一种基于改进DeepSORT的目标跟踪与定位方法在原始DeepSORT算法中加入基于位置约束的匹配,解决了因外观改变导致的漏匹配问题;在获取跟踪信息的基础上,设计了基于目标运动模型的相对定位方法,解决了图像中目标较小时相对定位不连续且定位精度较低的问题。试验结果表明,与传统DeepSORT算法相比,多目标跟踪准确度提高了5.9%;与仅依靠对齐点云的相对定位算法相比,定位精度提高了62.4%。     

惯性/视觉/激光雷达SLAM技术综述CSCD

同时定位与建图(SLAM)技术已广泛应用于各类自主移动平台中,其中视觉SLAM和激光雷达SLAM是两种主要的SLAM技术方案。然而,视觉SLAM系统易受视觉环境变化的影响,而激光雷达SLAM系统则在结构单一等环境中会出现精度退化甚至失效的情况。随着智能移动平台应用场景的不断拓展,对SLAM系统的精度和鲁棒性等提出了更高要求,将多种具有互补性的传感器进行融合是提升SLAM系统性能的有效途径。据此,聚焦惯性/视觉/激光雷达多传感器融合SLAM技术,从多传感器标定和多源数据融合两个主要方面进行综述,最后对多传感器融合SLAM技术的发展趋势进行了展望。     

基于视觉引导的无人直升机着舰技术研究

以无人直升机为被控对象,根据实际着舰流程研究了视觉引导系统的软硬件架构。在硬件上通过在摄像头加装云台,避免了无人机因姿态改变造成视野中目标图像的丢失,提高了位姿解算的精度。提出一种以红外灯设计的合作目标图案为着舰目标的视觉引导着舰系统,能够在不同光线强度、复杂周边环境下成功识别合作目标,具有良好的抗噪能力。研究设计了一套图像处理与位姿解算的引导系统,通过实验验证姿态参数的误差在2°以内,位置参数的误差小于2cm,能够满足着舰的精度要求;每帧图像的处理速度在30ms左右,具有良好的实时性。     

基于立体视觉的无人机位姿测量方法

现有的无人机位姿视觉测量方法大多基于诸如关键点等几何尺寸在图像和模型间的对应关系完成位姿计算;然而,在复杂情况下易出现关键点图像坐标定位失效的问题,而针对特定机型的算法设计泛化性不佳。针对这一问题,本文提出了一种基于立体视觉的固定翼无人机位姿测量方法,通过立体视觉重建目标无人机三维点云,基于无人机组件三维点云拟合鲁棒地完成位姿测量。首先,使用一种二维、三维数据结合的方式,利用卷积神经网络完成组件的分割。其次,分别利用机翼和机身点云拟合无人机坐标系的z轴和x轴,进而完成目标无人机位姿的计算。整个计算过程无需已知具体机型或尺寸。经试验验证,本文方法在10m的范围内达到了1.57°和0.07m的位姿测量精度,具有较高的精度和鲁棒性。     

多无人系统协同视觉SLAM算法

针对传统同时定位与地图构建(SLAM)方法受计算能力、存储能力的限制无法在大范围场景下作业,无法建立大范围场景的全局一致性地图等问题,基于ORB-SLAM2系统框架建立了一种中心式的多无人系统协同视觉SLAM算法。设计了地图大小限制策略,以保证无人系统不受机载设备算力和存储能力的影响,基于字典机制和Sim3转换构建了地图融合优化算法,以完成全局地图构建与优化。最后进行了数据集测试,结果表明：所提出算法能够完成多无人系统协同SLAM,相对传统SLAM算法具有明显优势。     

基于机器视觉的目标识别分类方法

工业现场生产的产品批量小、更新快、品种多,存在工作效率低、检测或识别质量得不到保证等问题。为了解决此问题,提出了一种基于机器视觉的目标识别分类方法。采用线阵相机,通过控制产品运动,获取产品表面完整的信息图像,利用多层感知器对图像拼接和处理后的字符进行识别,确定产品型号及批次,引导机器人完成产品的准确分类。实验结果表明,方法识别时间18 ms,识别准确率98%,可有效解决人工作业的各种问题。     

合作环境下基于惯性/里程计/Lidar融合的UGV导航方法

近年来，无人车在巡检、探测等方面的应用愈发广泛,且应用环境愈发复杂。在这些应用中，无人车必须对自身的位姿进行准确估计，以确保作业安全、高效完成。其中，可在复杂环境下适用的自主导航能力是核心关键技术。提出了一种基于惯性/里程计/激光雷达的地面无人车导航方法，区别于传统的激光雷达SLAM方法，该方法根据已知的几何结构特征进行定位，避免了因有效点数量稀少而导致的匹配误差。同时对惯性/里程计/激光雷达的融合算法进行了研究，提高了自主导航系统的鲁棒性和准确性。最后，在Gazebo中搭建了相应的仿真环境，并进行了算法验证。仿真结果表明，该方法能够实现无人车在巡检过程中实时可靠的自主导航，具有较好的工程应用价值。     

一种特殊领域无人靶车控制系统的设计

为了使特殊领域训练车辆实现无人靶车控制,利用开源技术控制系统,并修改现有无线数据传输协议以满足新的数据传输需求,采用GPS/RTK定位提升无人车户外规划路径行走的准确性,使用超声波装置实现无人车障碍物避免功能.结果表明使用开源技术架构设计能够实现特殊领域无人靶车的自动驾驶控制.研究结果为后续产品的升级开发提供可能.     

基于四元数的单目视觉物体位姿测量方法

对基于点特征的单目视觉定位算法进行了研究,设计了一种5点平面靶标,在五个特征点的基础上提出了一种基于四元数的单摄像机位姿测量方法。建立了四元数空间变换矩阵,然后再根据特征点在世界坐标系下的坐标值以及特征点在CCD成像面上的坐标值,在空间投射的基础上利用最小二乘法求解出靶标的四元数空间变换矩阵,从而求得靶标的空间位姿。通过实验对该单目视觉定位方法进行验证,实验结果表明：测量模型平移定位精度达到了,旋转定位精度达到了。     

Three-dimensional path planning for unmanned aerial vehicle based on interfered fluid dynamical system

This paper proposes a method for planning the three-dimensional path for low-flying unmanned aerial vehicle(UAV) in complex terrain based on interfered fluid dynamical system(IFDS) and the theory of obstacle avoidance by the flowing stream. With no requirement of solutions to fluid equations under complex boundary conditions, the proposed method is suitable for situations with complex terrain and different shapes of obstacles. Firstly, by transforming the mountains, radar and anti-aircraft fire in complex terrain into cylindrical, conical, spherical, parallelepiped obstacles and their combinations, the 3D low-flying path planning problem is turned into solving streamlines for obstacle avoidance by fluid flow. Secondly, on the basis of a unified mathematical expression of typical obstacle shapes including sphere, cylinder, cone and parallelepiped, the modulation matrix for interfered fluid dynamical system is constructed and 3D streamlines around a single obstacle are obtained. Solutions to streamlines with multiple obstacles are then derived using weighted average of the velocity field. Thirdly, extra control force method and virtual obstacle method are proposed to deal with the stagnation point and the case of obstacles’ overlapping respectively. Finally, taking path length and flight height as sub-goals, genetic algorithm(GA) is used to obtain optimal 3D path under the maneuverability constraints of the UAV. Simulation results show that the environmental modeling is simple and the path is smooth and suitable for UAV. Theoretical proof is also presented to show that the proposed method has no effect on the characteristics of fluid avoiding obstacles.     

Timeliness optimization of unmanned aerial vehicle lossy communications for internet-of-things

Information freshness is a key factor for Internet-of-Things(Io T) to make appropriate decisions and operations. This paper proposes an analytical framework for evaluating the timeliness performance of the Io T system based on Unmanned Aerial Vehicle(UAV) lossy communications.The performance analysis consists of the outage probability analysis and the Age-of-Information(Ao I) analysis with outages. To begin with, we solve a lossy coding problem formulated from the UAV communication system, and d...     

无人机油箱地面洗涤惰化性能

提出了无人机油箱地面洗涤惰化技术理论和方法,利用CFD方法研究了采用地面洗涤惰化技术降低油箱气相空间氧体积分数并使无人机油箱在地面和飞行条件下仍然保持惰化状态的可行性.利用vol-ume of fluid(VOF)两相流模型和自定义传质方程计算了不同油箱初始氧体积分数和载油率下气相空间氧体积分数的变化情况,结果表明:在...     

General optimal design of solar-powered unmanned aerial vehicle for priority considering propulsion system

This paper describes the general optimization design method of Solar-Powered Unmanned Aerial Vehicle which priority considering propulsion system planning. Based on the traditional solar powered aircraft design method, the propulsion system top-level target parameters which affect the path planning are integrated into the general optimization design. According to the typical mission requirements of Solar-Powered Unmanned Aerial Vehicle, considering the design variables such as wing area, aspect ...     

Robustness evaluation method for unmanned aerial vehicle swarms based on complex network theory

Unmanned Aerial Vehicle (UAV) swarms have been foreseen to play an important role in military applications in the future, wherein they will be frequently subjected to different disturbances and destructions such as attacks and equipment faults. Therefore, a sophisticated robustness evaluation mechanism is of considerable importance for the reliable functioning of the UAV swarms. However, their complex characteristics and irregular dynamic evolution make them extremely challenging and uncertain to evaluate the robustness of such a system. In this paper, a complex network theory-based robustness evaluation method for a UAV swarming system is proposed. This method takes into account the dynamic evolution of UAV swarms, including dynamic reconfiguration and information correlation. The paper analyzes and models the aforementioned dynamic evolution and establishes a comprehensive robustness metric and two evaluation strategies. The robustness evaluation method and algorithms considering dynamic reconfiguration and information correlation are developed. Finally, the validity of the proposed method is verified by conducting a case study analysis. The results can further provide some guidance and reference for the robust design, mission planning and decision-making of UAV swarms.     

基于LQG/LTR的高超声速飞行器全通道姿态控制

针对高超声速飞行器具有强烈的非线性、耦合及不确定性等特点,且存在系统噪声和量测噪声,使姿态控制变得困难的问题,提出了采用LQG/LTR控制方法进行全通道姿态控制的思路。首先,在平衡点通过小偏差线性化方法建立多变量耦合的控制模型;然后,运用LQG/LTR控制方法设计姿态控制器。仿真结果表明,在有高斯噪声情况下,所设计的姿态控制系统实现了指令精确跟踪,具有较强的鲁棒性。     

Computational engineering analysis of external geometrical modifications on MQ-1 unmanned combat aerial vehicle

This paper focuses on the effects of external geometrical modifications on the aerodynamic characteristics of the MQ-1 predator Unmanned Combat Aerial Vehicle(UCAV) using computational fluid dynamics. The investigations are performed for 16 flight conditions at an altitude of7.6 km and at a constant speed of 56.32 m/s. Two models are analysed, namely the baseline model and the model with external geometrical modifications installed on it. Both the models are investigated for various angles of at...     

小型无人机L1自适应纵向控制设计

针对小型无人机模型的不确定性以及传统模型参考自适应控制瞬态性能差的不足,采用一种新的L1自适应控制方法对小型无人机进行纵向俯仰角控制设计.首先研究了L1自适应控制方法的基本数学理论及其在一般不确定系统中的应用;考虑存在不确定因素时的小型无人机纵向模型,利用L1自适应控制方法设计了小型无人机纵向俯仰角的控制器;最后对所设...     

An intelligent target detection method of UAV swarms based on improved KM algorithm

Complete and efficient detection of unknown targets is the most popular application of UAV swarms. Under most situations, targets have directional characteristics so that they can only be successfully detected within specific angles. In such cases, how to coordinate UAVs and allocate optimal paths for them to efficiently detect all the targets is the primary issue to be solved. In this paper, an intelligent target detection method is proposed for UAV swarms to achieve real-time detection requirements. First, a target-feature-information-based disintegration method is built up to divide the search space into a set of cubes. Theoretically, when the cubes are traversed, all the targets can be detected. Then, a Kuhn-Munkres (KM)-algorithm-based path planning method is proposed for UAVs to traverse the cubes. Finally, to further improve search efficiency, a 3D real-time probability map is established over the search space which estimates the possibility of detecting new targets at each point. This map is adopted to modify the weights in KM algorithm, thereby optimizing the UAVs’ paths during the search process. Simulation results show that with the proposed method, all targets, with detection angle limitations, can be found by UAVs. Moreover, by implementing the 3D probability map, the search efficiency is improved by 23.4%–78.1%.     

面向未知区域深度测量的序列图像稠密点特征生成算法

对未知着降区平坦度测量是无人机在复杂地形下安全着陆的关键问题。首先,根据小孔成像原理推导出基于单目序列图像的未知区域深度计算方程;其次,针对稀疏匹配存在深度信息重构误差大而稠密匹配在平滑区域误匹配率高的问题,提出一种基于Delaunay三角剖分的稠密点特征生成算法;然后,分别对序列图像中的2帧图像提取亚像素级Harris角点和尺度不变特征变换(SIFT)特征点,并分别进行特征点匹配;再以2种特征点间的欧氏距离作为约束条件将2种特征点进行融合,生成准稠密特征点;最后,将准稠密特征点进行Delaunay三角剖分,并根据每个剖分三角形上3个顶点像素偏差的方差值制定稠密特征点的生成策略,并结合所提出的深度计算方程计算整个未知区域各点的深度信息。通过Vega Prime(VP)搭建仿真演示验证系统,实验结果表明在机载相机距地面400m处计算高度分别为90m和55m的物体深度信息时,其深度测量相对误差不超过0.89%,具有较高的精度。