# bumblebee_xb3

**Repository Path**: pete_peng/bumblebee_xb3

## Basic Information

- **Project Name**: bumblebee_xb3
- **Description**: ROS driver for the point grey Bumblebee XB3 Stereo Camera
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-10-19
- **Last Updated**: 2021-10-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

README for using the bumblebee_xb3 ros package

0. If you don't have camera calibration files, you can use the ones in
./calibration_files/ These need to be copied to the default directory
where ros stores camera calibration files, usually ~/.ros/camera_info/

1. Start ros:

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$ roscore
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2. In another terminal tab, launch the camera1394 driver node
(Ctrl+Shift+Tab to launch a new terminal tab and Alt+tab_number to move to a tab quickly)

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$ roslaunch ~/catkin_ws/src/bumblebee_xb3/launch/camera1394_24bit.launch
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For reference, the contents of the above launch file. It starts a camera1394 node with some parameters.
<!-- -*- mode: XML -*- -->
<launch>
<node pkg="camera1394" type="camera1394_node" name="camera1394_node" output="screen">
    <param name="video_mode" value="format7_mode3" />
    <param name="format7_color_coding" value="rgb8" />
    <param name="bayer_pattern" value="gbrg" />
    <param name="bayer_method" value="" />
    <param name="frame_id" value="camera_frame" />
    <param name="frame_rate" value="15.0" />
    <param name="iso_speed" value="800" /> 
</node> 
</launch>

once this node is launched, it will publish a interlaced (combined) bayered image which you can view by:
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$ rosrun rqt_image_view rqt_image_view image:=/camera/image_raw
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3. Next run the deinterlacer (& debayering) node (this package's node):
Note that this node only does deinterlacing. debayering is handled by
stereo_image_proc. 

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$ rosrun bumblebee_xb3 bumblebee_xb3_node
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Now running
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$ rostopic list
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should show you a lot more image streams, which you can again view with rqt_image_view

4. Now start the stereo_image_proc node in any of the THREE stereo_camera namespaces, say:

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$ ROS_NAMESPACE=/camera/stereo_camera_LC/ rosrun stereo_image_proc stereo_image_proc
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You should see that the point cloud topic is now published
/camera/stereo_camera_LC/points2

5. To view the point cloud, start rviz:

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$ rosrun rviz rviz
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COMMENTS:
stereo_image_proc uses a lot of cpu resources. consider using stereo_image_proc_gpu 
when it becomes available. 

Steps 1-4 can be combined into a single launch file for convenience.