公开(公告)号：US20160363451A1

公开(公告)日：2016-12-15

申请号：US15105459

申请日：2015-02-10

Applicant: HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Tianxu ZHANG ,  Sufei FAN ,  Yimeng CHEN ,  Heng YAO ,  Zhengtao LI ,  Zheng WANG ,  Wei HUANG ,  Zhenghua HUANG

IPC: G01C21/20

CPC classification number: G01C21/20 ,  B64G1/24 ,  G01C3/14 ,  G01S17/023 ,  G01S17/08 ,  G01S17/875 ,  G06T7/70 ,  G06T2207/10021 ,  G06T2207/30261

Abstract: The present invention discloses a multi-sensor merging based super-close distance autonomous navigation apparatus and method. The apparatus includes a sensor subsystem, an information merging subsystem, a sensor scanning structure, and an orientation guiding structure, wherein a visible light imaging sensor and an infrared imaging sensor are combined together, and data are acquired by combining a passive measurement mode composed of an optical imaging sensor and an active measurement mode composed of a laser distance measuring sensor. Autonomous navigation is divided into three stages, that is, a remote distance stage, implemented by adopting a navigation mode where a binocular visible light imaging sensor and a binocular infrared imaging sensor are combined, a close distance stage, implemented by adopting a navigation mode where a binocular visible light imaging sensor, a binocular infrared imaging sensor and a laser distance measuring sensor array are combined, and an ultra-close distance stage, implemented by adopting a navigation mode of a laser distance measuring sensor array. Through the present invention, the field of view and the exploration range are widened, the problem of shielding existing in passive measurement is effectively solved, the precision of data measurement is ensured, and the navigation efficiency and the safety and reliability of navigation are improved.

Abstract translation: 本发明公开了一种基于多传感器合并的超近距离自主导航装置和方法。 该装置包括传感器子系统，信息合并子系统，传感器扫描结构和定向引导结构，其中可见光成像传感器和红外成像传感器组合在一起，并且通过组合由 光学成像传感器和由激光测距传感器组成的主动测量模式。 自主导航分为三个阶段，即通过采用双目可见光成像传感器和双目红外成像传感器组合的导航模式实现的远距离舞台，近距离舞台，采用导航模式 将双目可见光成像传感器，双目红外成像传感器和激光距离测量传感器阵列组合在一起，并采用激光测距传感器阵列的导航模式实现的超近距离级。 通过本发明，扩大了视野和探索范围，有效解决了被动测量中存在的屏蔽问题，确保了数据测量的精度，提高了导航效率和导航的安全可靠性。

公开(公告)号：US20150242700A1

公开(公告)日：2015-08-27

申请号：US14711755

申请日：2015-05-13

Applicant: Huazhong University of Science and Technology

Inventor： Tianxu ZHANG ,  Sufei FAN ,  Yimeng CHEN ,  Yayun ZHENG ,  Changsheng CHEN ,  Zheng WANG ,  Huan WU ,  Xudong HE

IPC: G06K9/46 ,  G06T7/00 ,  G06K9/48

CPC classification number: G06K9/4604 ,  G06K9/481 ,  G06T7/269 ,  G06T7/66 ,  G06T2200/04 ,  G06T2207/10012 ,  G06T2207/10021 ,  G06T2207/30241

Abstract: A method for estimating a rotation axis and a mass center of a spatial target based on binocular optical flows. The method includes: extracting feature points from binocular image sequences sequentially and respectively, and calculating binocular optical flows formed thereby; removing areas ineffective for reconstructing a three-dimensional movement trajectory from the binocular optical flows of the feature points, whereby obtaining effective area-constrained binocular optical flows, and reconstructing a three-dimensional movement trajectory of a spatial target; and removing areas with comparatively large errors in reconstructing three-dimensional motion vectors from the optical flows by multiple iterations, estimating a rotation axis according to a three-dimensional motion vector sequence of each of the feature points obtained thereby, obtaining a spatial equation of an estimated rotation axis by weighted average of estimated results of the feature points, and obtaining spatial coordinates of a mass center of the target according to two estimated rotation axes.

Abstract translation: 一种用于基于双目光学流量估计空间目标的旋转轴线和质量中心的方法。 该方法包括：依次分别从双目图像序列中提取特征点，并计算由此形成的双目光学流; 从特征点的双目光流中去除重建三维运动轨迹的区域，从而获得有效面积约束的双目光学流，并重建空间目标的三维运动轨迹; 以及通过多次迭代从光流重建三维运动矢量中去除具有相对较大误差的区域，根据由其获得的每个特征点的三维运动矢量序列估计旋转轴，获得空间方程 通过估计结果的特征点的加权平均值估计旋转轴，并且根据两个估计的旋转轴获得目标的质心的空间坐标。

公开(公告)号：US20160363653A1

公开(公告)日：2016-12-15

申请号：US15106700

申请日：2015-02-10

Applicant: HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Tianxu ZHANG ,  Heng YAO ,  Peng JIANG ,  Sufei FAN ,  Yimeng CHEN ,  Wenxuan MA ,  Longwei HAO ,  Zhihui YANG

IPC: G01S7/48 ,  G01S17/93 ,  G01S17/02 ,  G01S17/89

CPC classification number: G01S7/4802 ,  G01S17/023 ,  G01S17/107 ,  G01S17/89 ,  G01S17/933 ,  G06K9/0063 ,  G06K9/00637

Abstract: The present invention provides an above-ground building recognition method, including the following steps: (1) taking an infrared image of the ground from the air; (2) performing detection and positioning in the infrared image to determine a suspected target; (3) aiming at the suspected target to perform laser imaging; (4) performing range gating on a laser image to filter out foreground and background interference; and (5) extracting a shape feature of the suspected target from the laser image with interference filtered out, and taking the shape feature as a target matching element to perform matching with a target shape feature template, so as to recognize the target. In the method of the present invention, laser imaging is integrated into infrared imaging target positioning, so that an advantage of a large range of infrared imaging is utilized, and three-dimensional range information of laser imaging is also utilized, thereby effectively improving the precision of positioning a building.

Abstract translation: 本发明提供了一种地面建筑识别方法，包括以下步骤：（1）从空中拍摄地面的红外图像; （2）执行红外图像的检测和定位以确定可疑目标; （3）瞄准可疑目标进行激光成像; （4）对激光图像进行范围选通，滤除前景和背景干扰; 并且（5）从具有被滤除的干扰的激光图像中提取可疑目标的形状特征，并且将形状特征作为目标匹配元素来执行与目标形状特征模板的匹配，以便识别目标。 在本发明的方法中，激光成像被集成到红外成像目标定位中，因此利用了大范围的红外成像的优点，并且还利用了激光成像的三维范围信息，从而有效地提高了精度 定位建筑物。

公开(公告)号：US20160189349A1

公开(公告)日：2016-06-30

申请号：US14964559

申请日：2015-12-09

Applicant: Huazhong University of Science and Technology

Inventor： Tianxu ZHANG ,  Zheng WANG ,  Li HE ,  Li LIU ,  Xuan HOU ,  Chuan ZHANG ,  Sufei FAN ,  Yimeng CHEN

IPC: G06T5/00 ,  G06T5/40 ,  G06F17/30 ,  G06T5/20

CPC classification number: G06T5/002 ,  G06T5/10 ,  G06T7/11 ,  G06T7/136 ,  G06T7/155 ,  G06T2207/20056 ,  G06T2207/30184

Abstract: A de-noising method for remote images of ground buildings using spectrum constraints. The method includes: 1) obtaining a reference image of ground buildings from a remote image database of the ground buildings, performing a Fourier transformation on the reference image to obtain an amplitude spectrum, and performing a threshold segmentation, an erosion operation and a dilation operation successively on the amplitude spectrum to obtain a binary template of spectrum of the ground buildings; and 2) obtaining a real-time image of the ground buildings by a high-speed aircraft, performing a Fourier transformation on the real-time image to obtain a spectrum, filtering the spectrum of the real-time image in frequency domain by the binary template of spectrum of the ground buildings, and performing an inverse Fourier transformation thereon to generate a filtered real-time image of the ground buildings.

Abstract translation: 使用频谱约束的地面建筑物远距离图像的去噪方法。 该方法包括：1）从地面建筑物的远程图像数据库获取地面建筑物的参考图像，对参考图像进行傅立叶变换以获得振幅谱，并执行阈值分割，侵蚀操作和扩张操作 连续振幅谱，得到地面建筑物光谱二元模板; 和2）通过高速飞行器获得地面建筑物的实时图像，对实时图像进行傅立叶变换以获得频谱，通过二进制码对频域中的实时图像的频谱进行滤波 地面建筑物的光谱模板，并对其进行逆傅里叶变换，以产生地面建筑物的滤波实时图像。