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Ubuntu Development System Configuration

• OpenCV
• PCL
• ROS
• Qt
• Flycapture
• Triclops
• ZJU-Repository Mirror Source

Stereo Camera Calibration

$ rosrun camera_calibration cameracalibrator.py --size 12x9 --square 0.05 right:=/camera/right/image_raw left:=/camera/left/image_raw right_camera:=/camera/right left_camera:=/camera/left

注：其中，12x9表示标定板横向和纵向的角点数；0.05表示标定板格子的边长，单位是米。

标定前效果：

标定后效果：

launch bumblebee2 stereo camera

$ roslaunch pointgrey_camera_driver bumblebee.launch

如下是一个可用的bumblebee.launch

<launch>  <!-- Determine this using rosrun pointgrey_camera_driver list_cameras.       If not specified, defaults to first camera found. -->  <arg name="bumblebee_serial" default="0" />  <arg name="calibrated" default="1" />  <group ns="camera">    <node pkg="nodelet" type="nodelet" name="bumblebee_nodelet_manager" args="manager" />    <node pkg="nodelet" type="nodelet" name="bumblebee_nodelet"          args="load pointgrey_camera_driver/PointGreyStereoCameraNodelet bumblebee_nodelet_manager" >      <param name="frame_id" value="bumblebee" />      <param name="frame_rate" value="15" />      <param name="first_namespace" value="left" />      <param name="second_namespace" value="right" />      <!-- When without this statement, the image publishing activity may be wrong. -->      <param name="format7_color_coding" value="raw16" />      <param name="serial" value="$(arg bumblebee_serial)" />      <!-- Use the camera_calibration package to create these files -->      <param name="camera_info_url" if="$(arg calibrated)"             value="file://$(env HOME)/.ros/camera_info/bb208s2c38_left.yaml" />      <param name="second_info_url" if="$(arg calibrated)"             value="file://$(env HOME)/.ros/camera_info/bb208s2c38_right.yaml" />    </node>    <node pkg="nodelet" type="nodelet" name="image_proc_debayer_left"        args="load image_proc/debayer bumblebee_nodelet_manager">      <remap from="image_raw" to="left/image_raw"/>      <remap from="image_mono" to="left/image_mono"/>      <remap from="image_color" to="left/image_color"/>    </node>    <node pkg="nodelet" type="nodelet" name="image_proc_debayer_right"        args="load image_proc/debayer bumblebee_nodelet_manager">      <remap from="image_raw" to="right/image_raw"/>      <remap from="image_mono" to="right/image_mono"/>      <remap from="image_color" to="right/image_color"/>    </node>  </group></launch>

注1：bb208s2c38_left.yaml和bb208s2c38_right.yaml分别是双目相机的标定文件。
注2：默认的bumblebee.launch如果没有指定Bumblebee2相机图像的格式，这可能导致ROS无法持续采集图像。

run stereo_image_proc node

$ ROS_NAMESPACE=camera rosrun stereo_image_proc stereo_image_proc

注：务必指定名字空间，以确保节点订阅到正确的话题。

查看视差图像：

$ rosrun image_view disparity_view image:=/camera/disparity

run libviso2 node

$ rosrun viso2_ros stereo_odometer stereo:=camera image:=image_rect

注：务必正确映射名字空间。

$ roslaunch '/home/robot/catkin_ws/src/drivers/pointgrey_camera_driver-master/fake_tf.launch'

注：此句是为了坐标变换。

ORB-SLAM2

• run ORB-SLAM2 Monocular node

$ rosrun ORB_SLAM2 Mono /home/exbot/robot/ORB_SLAM2-master/Vocabulary/ORBvoc.txt /home/exbot/robot/ORB_SLAM2-master/Examples/Monocular/xtion_as_mono.yaml /camera/image_raw:=/camera/rgb/image_rect_color

注1：Take Xtion’ s rgb channel as mono.
注2：由此可见，重映射话题名是个很容易的事情，可以在.launch文件中用标签指示，可以在命令行直接赋值，也可以在节点源文件中指定函数参数。
如下是一个可用的xtion_as_mono.yaml

%YAML:1.0#--------------------------------------------------------------------------------------------# Camera Parameters. Adjust them!#--------------------------------------------------------------------------------------------# Camera calibration and distortion parameters (OpenCV) Camera.fx: 518.0236Camera.fy: 515.6649Camera.cx: 316.4371Camera.cy: 247.8384Camera.k1: 0.0219Camera.k2: -0.1336Camera.p1: 0.0079Camera.p2: -0.0043Camera.k3: 0# Camera frames per second Camera.fps: 30.0  # If you want to get this value, you can test it with 'rostopic hz'                  # Yes, it is almost 30Hz.# Color order of the images (0: BGR, 1: RGB. It is ignored if images are grayscale)Camera.RGB: 1#--------------------------------------------------------------------------------------------# ORB Parameters#--------------------------------------------------------------------------------------------# ORB Extractor: Number of features per imageORBextractor.nFeatures: 1000# ORB Extractor: Scale factor between levels in the scale pyramid   ORBextractor.scaleFactor: 1.2# ORB Extractor: Number of levels in the scale pyramid  ORBextractor.nLevels: 8# ORB Extractor: Fast threshold# Image is divided in a grid. At each cell FAST are extracted imposing a minimum response.# Firstly we impose iniThFAST. If no corners are detected we impose a lower value minThFAST# You can lower these values if your images have low contrast           ORBextractor.iniThFAST: 20ORBextractor.minThFAST: 7#--------------------------------------------------------------------------------------------# Viewer Parameters#--------------------------------------------------------------------------------------------Viewer.KeyFrameSize: 0.05Viewer.KeyFrameLineWidth: 1Viewer.GraphLineWidth: 0.9Viewer.PointSize:2Viewer.CameraSize: 0.08Viewer.CameraLineWidth: 3Viewer.ViewpointX: 0Viewer.ViewpointY: -0.7Viewer.ViewpointZ: -1.8Viewer.ViewpointF: 500

• run ORB-SLAM2 Stereo node

$ rosrun ORB_SLAM2 Stereo /home/exbot/robot/ORB_SLAM2-master/Vocabulary/ORBvoc.txt /home/exbot/robot/ORB_SLAM2-master/Examples/Stereo/bb2.yaml false

注1：Take Bumblebee2-08S2C38 as sensor.
注2：这里最后一个参数false表示所订阅的左右图像已经是校正过的了，也就不需要根据bb2.yaml中的畸变参数进行校正了。

驱动 Hokuyo UTM-30LX-EW(Ethernet)

首先，安装驱动包，命令如下：

$ sudo apt-get install ros-indigo-urg-node

然后，配置主机的IP地址，与Hokuyo的IP处于同一局域网即可，例如：192.168.0.2。
至此，就可以运行驱动程序了，命令如下：

$ rosrun urg_node urg_node _ip_address:="192.168.0.10"

注：这里，指定了hokuyo的IP地址。
本部分参考链接