WO2020220628A1 - 一种基于激光线扫描成像的测距方法 - Google Patents

一种基于激光线扫描成像的测距方法 Download PDF

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WO2020220628A1
WO2020220628A1 PCT/CN2019/115033 CN2019115033W WO2020220628A1 WO 2020220628 A1 WO2020220628 A1 WO 2020220628A1 CN 2019115033 W CN2019115033 W CN 2019115033W WO 2020220628 A1 WO2020220628 A1 WO 2020220628A1
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laser
line
scanning
laser line
method based
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张永兵
黄熹之
季向阳
王好谦
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清华大学深圳国际研究生院
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Priority to US17/355,182 priority Critical patent/US11620760B2/en

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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S11/00Systems for determining distance or velocity not using reflection or reradiation
    • G01S11/12Systems for determining distance or velocity not using reflection or reradiation using electromagnetic waves other than radio waves
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/50Depth or shape recovery
    • G06T7/521Depth or shape recovery from laser ranging, e.g. using interferometry; from the projection of structured light
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation
    • G06T11/003Reconstruction from projections, e.g. tomography
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10028Range image; Depth image; 3D point clouds
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2211/00Image generation
    • G06T2211/40Computed tomography
    • G06T2211/436Limited angle

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  • the invention belongs to the field of scene reconstruction and environment perception, and specifically relates to a technology for realizing distance measurement based on laser line scan imaging.
  • the sensors used in autonomous driving currently mainly include millimeter wave radar, lidar, and cameras.
  • the use of imaging methods to realize environmental perception has the advantages of large amount of information acquisition and low cost, but it is easy to be interfered by light scattering and reflection in severe weather such as rainy and foggy days, and even larger ranging and reconstruction error.
  • the purpose of the present invention is to improve the use of imaging to achieve scene reconstruction in the fields of automatic driving and the like, which is vulnerable to interference from harsh environments, and proposes a method of ranging and scene reconstruction based on laser line scan imaging.
  • the method for distance measurement and scene reconstruction based on laser line scan imaging includes the following steps:
  • the collected real scene scan image is fused and calculated with a priori reference pattern, and the distance information of surrounding objects is extracted to realize environmental perception.
  • the advantage of the present invention is that the line laser is used as the light source and the image of the corresponding waveband is collected, which can weaken the influence of light reflection and scattering under severe weather to a certain extent.
  • the rotating galvanometer and the high-speed camera are used to realize the fast scanning and image acquisition of the line laser, so as to realize real-time environmental perception.
  • Figure 1 is a schematic diagram of a real scene acquisition system
  • FIG. 2 is a schematic diagram of a priori information collection according to an embodiment of the present invention.
  • FIG. 3 is a schematic diagram of prior pattern collection of line laser imaging according to an embodiment of the present invention.
  • Fig. 4 is a schematic diagram of an improved acquisition system based on a rotating galvanometer according to an embodiment of the present invention.
  • Fig. 5 is a schematic flowchart of an embodiment of the present invention.
  • the following embodiments of the present invention use the line laser in the near-infrared band as the light source to quickly scan the surrounding scene, and use the camera to collect the imaging in the special band, and finally use these images to reconstruct the surrounding scene.
  • This method avoids radar ranging and can effectively save costs.
  • the imaging method is used to realize environmental perception.
  • line laser is used as the light source, and images of the corresponding band are collected, which can weaken the reflection and scattering of light in severe weather to a certain extent. influences.
  • Environmental perception technology based on imaging methods is widely used in research fields such as autonomous driving, but it is susceptible to interference caused by light scattering and reflection in harsh environments such as rain and fog, and even large errors in ranging and reconstruction.
  • this embodiment proposes a distance measurement method based on laser line scan imaging, which can effectively suppress the interference caused by extreme weather to imaging.
  • This method includes the following steps:
  • the collected real scene scan image is fused and calculated with a priori reference pattern, and the distance information of surrounding objects is extracted to realize environmental perception.
  • Figure 1 shows a schematic diagram of a real scene acquisition system.
  • the line laser and the camera are relatively fixed and at a certain angle.
  • the scanning method adopts overall rotation, that is, the laser source and the camera rotate together. In this way, the laser will hit different positions on the object surface during the rotation.
  • the x direction is the horizontal plane of the camera, that is, the wide plane of the captured image
  • the z direction is the depth plane of the camera, which is the distance of the surrounding environment that needs to be perceived.
  • the y direction is the high surface of the collected image
  • the line laser is a ray that is perpendicular to the x direction, parallel to the y direction, and hits the z direction. The person in the distance looks like a line instead of a point.
  • the object surface shown in Figure 1 is only the surface of the object along the x direction under a certain y value.
  • the line laser can detect the y value within a certain range (depending on the length of the line laser, the longitudinal resolution of the camera and the detection Distance), so as to be able to scan the surface of the object at a certain angle (depending on the angle range of the scan).
  • the line laser source and the camera rotate together, and an image is collected for each rotation angle.
  • the y-direction information of the image corresponds to the y-direction information of the acquisition system
  • the x-direction information of the image corresponds to the z-direction information of the acquisition system, that is
  • the distance information of the surrounding environment, and the x-direction information of the acquisition system depends on the scanning angle. For example, if the laser source and the camera are rotated by 30 degrees, the perception information of objects at a distance of 30 degrees with the rotation axis as the center can be obtained.
  • the distance measurement and scene reconstruction method based on laser line scan imaging includes the following steps, as shown in Figure 5:
  • the collected real scene scan image is fused and calculated with a priori reference pattern, and the distance information of surrounding objects is extracted to realize environmental perception.
  • the following introduces the principle that the imaging system uses the priori pattern and the acquired image to fuse operations to obtain the tomographic information for 3D reconstruction.
  • FIG. 2 shows the principle of a priori information collection.
  • Iz i (Ox 1 *Mx 1 z i +...+Ox 30 *Mx 30 z i )/(Mx 1 z i +...+Mx 30 z i )——(1)
  • the z i position represents the depth position of the tomographic information we need.
  • the maximum value of each pixel can be used to obtain the surface point cloud image of the object, and thus the reconstructed perception information can be obtained.
  • This algorithm uses the modulation characteristics of structured light imaging, the modulated pattern hits the object to obtain tomographic information and also uses the focal surface characteristics of the virtual confocal system. It is worth mentioning that the collection of a priori patterns only needs to be collected once for the same system and can be used in different scene reconstructions.
  • Figure 3 shows a schematic diagram of prior pattern acquisition in line laser imaging.
  • the scanning of the line array becomes the overall rotation of the imaging system, and the movement in the horizontal direction (x direction) becomes the deflection of the angle, so that the reconstructed point cloud image obtained is in the polar coordinate system.
  • the corresponding depth z j section information is Ox i Mz j
  • Figure 4 shows a schematic diagram of an improved acquisition system based on a rotating galvanometer.
  • a rotating galvanometer is added to quickly scan the line laser, and a high-speed camera is used to collect sampled images within a certain angle.
  • the improved imaging system has the functions of high-speed scanning and rapid modeling and perception.

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  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Optics & Photonics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Electromagnetism (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Measurement Of Optical Distance (AREA)

Abstract

一种基于激光线扫描成像的测距方法,能够有效抑制极端天气对成像造成的干扰,此方法包括以下步骤:对固定好的激光线扫描系统采集先验的参考图案,参考白板分别放置在不同距离远处,线激光打到白板由相机采集到参考图案(S1);将激光线扫描设备放置于真实场景中,对不同角度分别发射线激光,同时用相机采集每个扫描角度的图像(S2);利用基于激光线扫描的测距算法,将采集得到的真实场景扫描图像与先验参考图案融合计算,提取出周围物体的距离信息,实现环境感知(S3)。

Description

一种基于激光线扫描成像的测距方法 技术领域
本发明属于场景重建和环境感知领域,具体涉及一种基于激光线扫描成像实现测距的技术。
技术背景
自动驾驶所应用的传感器目前主要有毫米波雷达、激光雷达和摄像头等。其中采用成像方式来实现环境感知有获取信息量大、成本较低等优点,但在雨天、雾天等恶劣天气下容易受到光线散射、反射等情形造成的干扰,以至测距和重建出现较大误差。
发明内容
本发明的目的在于改进自动驾驶等领域中利用成像实现场景重建,而易受到恶劣环境干扰的不足,提出了一种基于激光线扫描成像的测距与场景重建的方法。
本发明提供的基于激光线扫描成像的测距与场景重建的方法包括以下步骤:
1)对固定好的激光线扫描系统采集先验的参考图案,参考白板分别放置在不同距离远处,线激光打到白板由相机采集到参考图案;
2)将激光线扫描设备放置于真实场景中,对不同角度分别发射线激光,同时用相机采集每个扫描角度的图像;
3)利用基于激光线扫描的测距算法,将采集得到的真实场景扫描图像与先验参考图案融合计算,提取出周围物体的距离信息,实现环境感知。
本发明的优点在于用线激光作为光源,并且采集相应波段的图像,能在一定程度上削弱恶劣天气下光线反射及散射的影响。同时利用旋转振镜和高速摄像头实现线激光的快速扫描和图像采集,从而进行实时的环境感知。
附图说明
图1为真实场景采集系统示意图;
图2为本发明实施例先验信息采集原理图;
图3为本发明实施例线激光成像先验图案采集示意图;
图4为本发明实施例改进的基于旋转振镜采集系统示意图。
图5是本发明实施例流程示意图。
具体实施方式
下面结合附图对本发明进一步说明。
本发明下述实施例利用近红外波段的线激光作为光源,快速扫描周边场景,并用相机 采集特殊波段下的成像,最后用这些图像进行周围场景的重建。此方法避免了雷达测距,能有效地节约成本,利用成像方法来实现环境感知,同时用线激光作为光源,并且采集相应波段的图像,能在一定程度上削弱恶劣天气下光线反射及散射的影响。
本发明下述实施例应用于场景重建与环境感知。基于成像方法的环境感知技术在自动驾驶等研究领域中广泛应用,但是在雨雾天气等恶劣环境下容易受到光线散射、反射等情形造成的干扰,以至测距和重建出现较大误差。
为此,本实施例提出一种基于激光线扫描成像的测距方法,能够有效抑制极端天气对成像造成的干扰,此方法包括以下步骤:
对固定好的激光线扫描系统采集先验的参考图案,参考白板分别放置在不同距离远处,线激光打到白板由相机采集到参考图案;
将激光线扫描设备放置于真实场景中,对不同角度分别发射线激光,同时用相机采集每个扫描角度的图像;
利用基于激光线扫描的测距算法,将采集得到的真实场景扫描图像与先验参考图案融合计算,提取出周围物体的距离信息,实现环境感知。
如图1所示为真实场景采集系统示意图。线激光和相机相对固定,并成一定角度。扫描方式采取整体旋转,即激光源和相机一同旋转。如此在旋转中线激光就会打到物体面的不同位置。示意图中x方向为相机的横面,即采集到的图像的宽面,z方向为相机的纵深面,即为需要感知的周边环境的距离。另外y方向为采集到图像的高面,而线激光是垂直于x方向、平行于y方向,向z方向打出去的一条光线,远处的人看上去是一条线而非一个点。故而图1中所示的物体面仅是某一个y值下物体沿x方向的表面,线激光能探测到一定范围内的y值(取决于线激光的长度、相机的纵向分辨率以及探测的距离),从而能够扫描远处一定角度(取决于扫描的角度范围)的物体的表面情形。
线激光源和相机一同旋转,每旋转一个角度就采集一张图像。假设每张图像的横向坐标为x轴,纵向坐标为y轴,则图像的y方向信息对应于采集系统的y方向信息,图像的x方向信息则会对应于采集系统的z方向信息,也就是周围环境的距离信息,而采集系统的x方向信息取决于扫描的角度。比如激光源和相机旋转了30度,则能够得到以旋转轴为中心的30度范围远处物体的感知信息。
基于激光线扫描成像的测距和场景重建方法,包括以下步骤,如图5所示:
1)对固定好的激光线扫描系统采集先验的参考图案,参考白板分别放置在不同深度,线激光分别从不同角度打到白板上由相机采集到参考图案。假设线激光扫描的角度分别是 X 1,X 2,……,X n,采样的深度分别是Z 1,Z 2,……,Z m
2)将激光线扫描设备放置于真实场景中,按照角度X 1,X 2,……,X n依次发射线激光,用相机采集每个角度的图像;
3)利用基于激光线扫描的测距算法,将采集得到的真实场景扫描图像与先验参考图案融合计算,提取出周围物体的距离信息,实现环境感知。
其中的大体的算法流程如下:
①获取采集系统的参考图案,其角度X 1-X n和深度Z 1-Z m,一共n*m张,记为M(X iZ j),其中i=1,2,……,n,j=1,2,……,m。
②真实场景中采集获得角度X 1-X n下的n张图像,记为O(X i),其中i=1,2,……,n。
③利用虚拟共聚焦成像的聚焦面特性,计算X i角度Z j深度的层析信息O(X i)*M(X iZ j),其中i=1,2,……,n,j=1,2,……,m。
④利用结构光成像的调制特性,获得X i角度下的表面深度,其计算公式为:
Z surf(X i)=argmax (Zj)(O(X i)*M(X iZ j)),其中i=1,2,……,n。
⑤利用表面深度Z surf(X i)重建物体的三维点云图,实现环境感知。
下面介绍成像系统利用先验图案与采集图像融合运算,从而得到层析信息进行三维重建的原理。
如下图2所示为先验信息采集原理,DMD调制装置发出将光线调制成线阵列模式,打到不同深度(z值)下的白板上由相机采集图像。假设线阵列的间距为30像素,则一共发射30个调制的线阵列,所有线阵列合起来正好铺满整个图像,保证采样信息的完整性,其位置记为x 1-x 30。在z=z 1位置上我们能够得到30幅参考图案,分别是30个调制的线阵列打到位于z=z 1位置的白板处,将其记为Mx 1z 1—Mx 30z 1。同理,我们也可以获得其他z位置的30幅参考图案。而在获得两个z位置(比如z 1位置和z 2位置)的参考图案后,我们可以预测其他z位置的图案,这样先验图案的采集只需要采集两个z位置即可。
在获得各个z位置的先验图案后,我们将系统应用于采集真实场景的图像。30个线阵列分别采集一张图像,记为Ox 1—Ox 30,于是我们可以计算得到z i位置的层析图像:
Iz i=(Ox 1*Mx 1z i+…+Ox 30*Mx 30z i)/(Mx 1z i+…+Mx 30z i)——(1)
其中z i位置表示我们所需要层析信息的深度位置,利用不同z位置的层析信息,在每个像素点取最大值即可得到物体的表面点云图,如此得到重建的感知信息。此算法利用到结构光成像的调制特性,调制后的图案打到物体上获得层析信息也利用到虚拟共聚焦系统的聚焦面特性。值得一提的是,先验图案的采集对于同样的系统只需要采集一次,便可应 用于不同的场景重建中。
如图3所示为线激光成像先验图案采集示意图。与以上的原理图不同的地方在于线阵列的扫描变为成像系统的整体旋转,横方向(x方向)的移动变为角度的偏转,这样得到的重建点云图则是处于极坐标系下。另外由于激光源和相机一同旋转,则对于不同角度下的先验图案而言是一致的,即Mx 1z i=Mx 2z i=……=Mx nz i=Mz i。此时对于角度x i而言,其对应的深度z j切面信息为Ox iMz j,则x i位置表面的深度为z surf=argmax (zj)(Ox iMz j)。如此便能把每个角度下的物体表面距离提取出来,从而重建三维点云图。
在自动驾驶的场景中,快速成像进行环境感知是必不可少的,利用图像来进行环境感知对硬件设施和计算速度都是一个考验,用激光线扫描来成像更是需要扫描和成像的速度。而激光源和摄像头同时旋转扫描显然大大限制了其成像速度,所以需考虑改进系统,利用振镜偏转来实现扫描,从而增加扫描和成像的速度。
如图4所示为改进的基于旋转振镜采集系统示意图,增加了旋转振镜使线激光快速扫描,利用高速摄像机采集某一角度内的采样图像。改进后的成像系统具有高速扫描,快速建模感知的功能。

Claims (10)

  1. 一种基于激光线扫描成像的测距方法,其特征在于,包括以下步骤:
    S1、对固定好的激光线扫描系统采集先验的参考图案;
    S2、将激光线扫描设备放置于真实场景中,按照线激光扫描的角度依次发射线激光,用相机采集每个角度的图像;
    S3、利用基于激光线扫描的测距算法,将采集得到的真实场景扫描图像与先验参考图案融合计算,提取出周围物体的距离信息,实现环境感知。
  2. 根据权利要求1所述的基于激光线扫描成像的测距方法,其特征在于,步骤S1中,采集时,参考白板分别放置在不同深度Z 1,Z 2,……,Z m,线激光分别从不同角度X 1,X 2,……,X n打到白板上由相机采集到参考图案。
  3. 根据权利要求1所述的基于激光线扫描成像的测距方法,其特征在于,线激光的扫描通过如下方法实现:光源发出垂直于地面的线激光,激光源和相机相对固定,并绕着垂直于地面的中心轴进行机械旋转。
  4. 根据权利要求1所述的基于激光线扫描成像的测距方法,其特征在于,线激光的扫描通过如下方法实现:将垂直于地面的线激光打到光源边的旋转振镜上并反射出去,通过振镜的快速转动实现线激光的扫描。
  5. 根据权利要求1所述的基于激光线扫描成像的测距方法,其特征在于,步骤S3中,其使用的算法结合了结构光成像的调制特性和虚拟共聚焦成像的聚焦面特性。
  6. 根据权利要求1所述的基于激光线扫描成像的测距方法,其特征在于,硬件上利用扫描线激光作为光源调制,重构时分离出层析信息,构建感知模型。
  7. 根据权利要求1所述的基于激光线扫描成像的测距方法,其特征在于,扫描的角度范围决定重构周围环境的角度,参考图案选取的深度范围决定重构的深度。
  8. 根据权利要求1所述的基于激光线扫描成像的测距方法,其特征在于,具体算法步骤如下:
    步骤S1中,获取采集系统的参考图案时,其角度X 1-X n和深度Z 1-Z m,一共n*m张,记为M(X iZ j),其中i=1,2,……,n,j=1,2,……,m;
    步骤S2中,真实场景中采集获得角度X 1-X n下的n张图像,记为O(X i),其中i=1,2,……,n;
    步骤S3中,利用虚拟共聚焦成像的聚焦面特性,计算X i角度Z j深度的层析信息O(X i)*M(X iZ j),
    其中i=1,2,……,n,j=1,2,……,m;
    利用结构光成像的调制特性获得X i角度下的表面深度;
    利用表面深度Zsurf(X i)重建物体的三维点云图,实现环境感知。
  9. 根据权利要求8所述的基于激光线扫描成像的测距方法,其特征在于,所述利用结构光成像的调制特性获得X i角度下的表面深度,其计算公式为:
    Zsurf(X i)=argmax(Z j)(O(X i)*M(X iZ j)),其中i=1,2,……,n。
  10. 一种基于激光线扫描的测距装置,包括存储器和处理器,其特征在于,所述存储器中存储有计算机程序,所述计算机程序可被处理器执行以实现如权利要求1至9中任一项所述的基于激光线扫描的测距方法。
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