ros下单目相机校正

1. 安装对应的驱动与程序包。

图像对应包 http://wiki.ros.org/camera_calibration 在gitbub下载image_pipeline ： https://github.com/ros-perception/image_pipeline

安装对应的驱动

1）uvc_camera ktossell/camera_umd
sudo apt-get install ros-indigo-xxxxx ( camera_umd jpeg_streamer uvc_camera )

2）usb_cam http://wiki.ros.org/usb_cam
bosch-ros-pkg/usb_cam

2. 相机校正的步骤

1）启动相机 uvc_camera 或者 usb_cam

roslaunch usb_cam camera.launch (个人的 camera.launch) rviz 详细文件见后。（也能够自己先打开rviz 加入topic后保存，以后直接调用保存的.rviz就可以）

camera.launch

<launch>

	<node pkg="rviz" type="rviz" name="rviz"

		args="-d $(find usb_cam)/launch/camera.rviz"/>		

	<node name="usb_cam" pkg="usb_cam" type="usb_cam_node" respawn="false" output="log">

		<param name="video_device" type="string" value="/dev/video0"/>

		<param name="camera_frame_id" type="string" value="usb_cam"/>

		<param name="framerate" type="int" value="30"/>

		<param name="io_method" type="string" value="mmap"/>

		<param name="image_width" type="int" value="640"/>

		<param name="image_height" type="int" value="480"/>

		<param name="pixel_format" type="string" value="yuyv"/>

	</node>

</launch>

2）启动校正程序

參见教程 http://wiki.ros.org/camera_calibration/Tutorials/MonocularCalibration

yhzhao@yhzhao:~$ rostopic list

/usb_cam/camera_info

/usb_cam/image_raw     ################################

/usb_cam/image_raw/compressed

/usb_cam/image_raw/compressed/parameter_descriptions

/usb_cam/image_raw/compressed/parameter_updates

/usb_cam/image_raw/compressedDepth

rosrun camera_calibration cameracalibrator.py --size 8x6 --square 0.0245 image:=/usb_cam/image_raw camera:=/camera

出错：例如以下

('Waiting for service', '/camera/set_camera_info', '...')

Service not found

执行例如以下语句：角点数棋盘格大小 topic映射

rosrun camera_calibration cameracalibrator.py --size 8x6 --square 0.0245 image:=/usb_cam/image_raw camera:=/camera --no-service-check

注意：校正採集的角点图像要多。数量达到一定效果时，calibration button会变亮，点击就可以进行校正运算。结果在终端有显示，也能够选择保存。

校正输出结果：

('D = ', [-0.1976212648687889, 0.1688022413942262, 0.0124442419926021, 0.005870906198680583, 0.0])

('K = ', [485.5897704187133, 0.0, 297.2537641560215, 0.0, 491.6813624489518, 296.2003190013238, 0.0, 0.0, 1.0])

('R = ', [1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0])

('P = ', [462.4408874511719, 0.0, 301.47298442859574, 0.0, 0.0, 469.7864074707031, 301.54598383033044, 0.0, 0.0, 0.0, 1.0, 0.0])

None

# oST version 5.0 parameters

[image]

width

640

height

480

[narrow_stereo]

camera matrix

485.589770 0.000000 297.253764

0.000000 491.681362 296.200319

0.000000 0.000000 1.000000

distortion

-0.197621 0.168802 0.012444 0.005871 0.000000

rectification

1.000000 0.000000 0.000000

0.000000 1.000000 0.000000

0.000000 0.000000 1.000000

projection

462.440887 0.000000 301.472984 0.000000

0.000000 469.786407 301.545984 0.000000

0.000000 0.000000 1.000000 0.000000

3. 启动 ros 相机相应节点公布图像topic

carmera_haved_calibrated.launch

<launch>

	<node pkg="rviz" type="rviz" name="rviz"

		args="-d $(find usb_cam)/launch/camera.rviz"/>		

	<node name="usb_cam" pkg="usb_cam" type="usb_cam_node" respawn="false" output="log">

		<param name="video_device" type="string" value="/dev/video0"/>

		<param name="camera_frame_id" type="string" value="usb_cam"/>

		<param name="io_method" type="string" value="mmap"/>

		<param name="image_width" type="int" value="640"/>

		<param name="image_height" type="int" value="480"/>

		<param name="pixel_format" type="string" value="yuyv"/>

		<rosparam param="D">[-0.1976212648687889, 0.1688022413942262, 0.0124442419926021, 0.005870906198680583, 0.0]</rosparam>

		<rosparam param="K">[485.5897704187133, 0.0, 297.2537641560215, 0.0, 491.6813624489518, 296.2003190013238, 0.0, 0.0, 1.0]</rosparam>

		<rosparam param="R">[1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0]</rosparam>

		<rosparam param="P">[462.4408874511719, 0.0, 301.47298442859574, 0.0, 0.0, 469.7864074707031, 301.54598383033044, 0.0, 0.0, 0.0, 1.0, 0.0]</rosparam>

	</node>

</launch>

------------------------------------------------------------附--------------------------------------------------------------------------------------------------------------------------------------

<pre name="code" class="html">$(find usb_cam)/launch/camera.rviz文件

Panels:

  - Class: rviz/Displays

    Help Height: 78

    Name: Displays

    Property Tree Widget:

      Expanded: ~

      Splitter Ratio: 0.5

    Tree Height: 144

  - Class: rviz/Selection

    Name: Selection

  - Class: rviz/Tool Properties

    Expanded:

      - /2D Pose Estimate1

      - /2D Nav Goal1

      - /Publish Point1

    Name: Tool Properties

    Splitter Ratio: 0.588679

  - Class: rviz/Views

    Expanded:

      - /Current View1

    Name: Views

    Splitter Ratio: 0.5

  - Class: rviz/Time

    Experimental: false

    Name: Time

    SyncMode: 0

    SyncSource: Image

Visualization Manager:

  Class: ""

  Displays:

    - Alpha: 0.5

      Cell Size: 1

      Class: rviz/Grid

      Color: 160; 160; 164

      Enabled: true

      Line Style:

        Line Width: 0.03

        Value: Lines

      Name: Grid

      Normal Cell Count: 0

      Offset:

        X: 0

        Y: 0

        Z: 0

      Plane: XY

      Plane Cell Count: 10

      Reference Frame: <Fixed Frame>

      Value: true

    - Class: rviz/Image

      Enabled: true

      Image Topic: /usb_cam/image_raw

      Max Value: 1

      Median window: 5

      Min Value: 0

      Name: Image

      Normalize Range: true

      Queue Size: 2

      Transport Hint: raw

      Value: true

    - Class: rviz/Image

      Enabled: true

      Image Topic: /slam/raw_flip_image

      Max Value: 1

      Median window: 5

      Min Value: 0

      Name: Image

      Normalize Range: true

      Queue Size: 2

      Transport Hint: raw

      Value: true

    - Class: rviz/Image

      Enabled: true

      Image Topic: /detect_qr/qr_img

      Max Value: 1

      Median window: 5

      Min Value: 0

      Name: Image

      Normalize Range: true

      Queue Size: 2

      Transport Hint: raw

      Value: true

    - Class: rviz/Image

      Enabled: true

      Image Topic: /slam/qrslam/slam_map

      Max Value: 1

      Median window: 5

      Min Value: 0

      Name: Image

      Normalize Range: true

      Queue Size: 2

      Transport Hint: raw

      Value: true

  Enabled: true

  Global Options:

    Background Color: 48; 48; 48

    Fixed Frame: odom

    Frame Rate: 30

  Name: root

  Tools:

    - Class: rviz/Interact

      Hide Inactive Objects: true

    - Class: rviz/MoveCamera

    - Class: rviz/Select

    - Class: rviz/FocusCamera

    - Class: rviz/Measure

    - Class: rviz/SetInitialPose

      Topic: /initialpose

    - Class: rviz/SetGoal

      Topic: /move_base_simple/goal

    - Class: rviz/PublishPoint

      Single click: true

      Topic: /clicked_point

  Value: true

  Views:

    Current:

      Class: rviz/Orbit

      Distance: 15.7352

      Enable Stereo Rendering:

        Stereo Eye Separation: 0.06

        Stereo Focal Distance: 1

        Swap Stereo Eyes: false

        Value: false

      Focal Point:

        X: 0

        Y: 0

        Z: 0

      Name: Current View

      Near Clip Distance: 0.01

      Pitch: 0.825398

      Target Frame: <Fixed Frame>

      Value: Orbit (rviz)

      Yaw: 1.5604

    Saved: ~

Window Geometry:

  Displays:

    collapsed: false

  Height: 718

  Hide Left Dock: false

  Hide Right Dock: false

  Image:

    collapsed: false

  QMainWindow State: 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

  Selection:

    collapsed: false

  Time:

    collapsed: false

  Tool Properties:

    collapsed: false

  Views:

    collapsed: false

  Width: 1855

  X: 90

  Y: 153

ros下单目相机校正的更多相关文章

基于OpenCV单目相机的快速标定--源码、工程、实现过程
相机的标定是所有人走进视觉世界需要做的第一件事,辣么多的视觉标定原理解释你可以随便在网上找到,这里只讲到底如何去实现,也算是给刚入门的朋友做个简单的分享. 1.单目相机标定的工程源码首先请到同性交友 ...
ROS与深度相机入门教程-在ROS使用kinect v1摄像头
ROS与深度相机入门教程-在ROS使用kinect v1摄像头说明: 介绍在ros安装和使用kinect v1摄像头介绍freenect包安装驱动 deb安装 $ sudo apt-get in ...
ROS标定IDS相机
参考 ROS 相机标定http://blog.csdn.net/ArtistA/article/details/51125560 ROS里的标定程序只要使用了OPNCV的标定程序: opencv 相机 ...
matlab单目相机标定——标定步骤以及参数含义
参考博客园的一篇文章: https://www.cnblogs.com/flyinggod/p/8470407.html#commentform
双目相机标定以及立体测距原理及OpenCV实现
单目相机标定的目标是获取相机的内参和外参,内参(1/dx,1/dy,Cx,Cy,f)表征了相机的内部结构参数,外参是相机的旋转矩阵R和平移向量t.内参中dx和dy是相机单个感光单元芯片的长度和宽度,是 ...
ZED 相机 && ORB-SLAM2安装环境配置与ROS下的调试
注:1. 对某些地方进行了更新(红色标注),以方便进行配置. 2. ZED ROS Wrapper官方github已经更新,根据描述新的Wrapper可能已经不适用与Ros Indigo了,如果大家想 ...
ORB-SLAM2实现（kinect V1/ROS）
实验室电脑环境ubuntu14.04和ROS indigo已经装好. 1. 构建工作空间[非常重要的一步] mkdir -p ~/catkin_ws/src cd ~/catkin_ws/ catki ...
单目、双目和RGB-D视觉SLAM初始化比较
无论单目.双目还是RGB-D,首先是将从摄像头或者数据集中读入的图像封装成Frame类型对象: 首先都需要将彩色图像处理成灰度图像,继而将图片封装成帧. (1) 单目 mCurrentFrame = ...
三维重建：深度相机方案对比-KinectFusion的基本原理（尺度）
算法原理请参考此文: kinect fusion 3D重建基本算法 http://log.csdn.net/xiaohu50/article/details/51592503 三维重建为三维空间实 ...

随机推荐

自动播放——幻灯片缓冲效果&&带Loading效果的图片切换&&移动效果（按轨迹移动）
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/ ...
内置函数new() 和struct{} 初始化的区别
一.new() 这是一个用来分配内存的内置函数,它的第一个参数是一个类型,不是一个值,它的返回值是一个指向新分配的 t 类型的零值的指针.在golang的代码定义如下: func new(t Type ...
springboot缓存及连接池配置
参见https://coding.imooc.com/lesson/117.html#mid=6412 1.springboot的springweb自己默认以及配置好了缓存,只需要在主文件(XxxAp ...
重启nginx后丢失nginx.pid的解决方法（转）
一,nginx的停止操作停止操作是通过向nginx进程发送信号来实现的.步骤1:查询nginx主进程号 ps -ef | grep nginx 在进程列表里面找master进程,它的编号就是主进程 ...
Servlet的API（一）
Servlet的API有很多,这里只谈谈两个Servlet对象:ServletConfig对象和ServletContext对象. 1. ServletConfig对象在Servlet的配置文件中, ...
Eclipse配色利器
1 http://eclipsecolorthemes.org/ 这是官网 2 安装后,window-preferences-general-appearance-color theme 即可找到多 ...
kafka 配置kerberos校验以及开启acl实践
转载请注明原创地址:http://www.cnblogs.com/dongxiao-yang/p/7131626.html kafka从0.9版本以后引入了集群安全机制,由于最近需要新搭建一套kafk ...
graph小案例
(小案例,有五个人他们参见相亲节目,这个五个人分别是0,1,2,3,4,号选手,计算出追随者年龄大于被追随者年龄的人数和平均年龄) scala> import org.apache.spark. ...
TCP粘包处理通用框架--C代码
说明:该文紧接上篇博文“ linux epoll机制对TCP 客户端和服务端的监听C代码通用框架实现 ”讲来 (1)TCP粘包处理数据结构设计 #define MAX_MSG_LEN 65535 ty ...
DataUml Design 教程1-初识
DataUml Design 是面向开发人员使用的一个永久免费的软件,提高软件的开发效率和代码的规范度.它主要包括三大功能,数据模型.代码生成和UML建模,数据模型功能类似于PowerDesi ...

ros下单目相机校正

ros下单目相机校正的更多相关文章

随机推荐

热门专题