USB Camera Introduction

1. Content Description

• Start the camera driver, view the camera image through rqt, and check the camera intrinsic parameters topic

2. Camera Introduction

3. Preparation

ros2 launch yahboomcar_bringup usb_camera.launch.py

4. Case Demonstration

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ros2 run rqt_image_view rqt_image_view

• Select the /image_raw topic to see the camera's RGB color image

• Check the camera intrinsic parameters topic

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ros2 topic echo /camera_info --once

• The camera's intrinsic parameters topic will be used in subsequent courses for functions such as Aruco marker pose solving and PnP pose solving

5. Source Code Analysis

• Launch path

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~/yahboomcar_ros2_ws/yahboomcar_ws/src/yahboomcar_bringup/launch/usb_camera.launch.py

• Parameter file

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~/yahboomcar_ros2_ws/yahboomcar_ws/src/yahboomcar_bringup/param/common.yaml

• common_params: loads the common.yaml configuration file through FilePathManager, including parameters such as the camera IO method and pixel format

• camera_info_file: concatenates the full path of the camera intrinsic parameters file usb_camera_info.yaml, adding the file:// prefix for the driver to load

• uasb_camera: starts the usb_cam_node_exe node, with the main parameters:

  • video_device: video device path /dev/video0

  • image_width / image_height: resolution 640×480

  • framerate: frame rate 30fps

  • camera_info_url: path of the intrinsic parameters file, used to publish the /camera_info topic

  • enable_rectify: enable image rectification

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def generate_launch_description():
    ld = LaunchDescription()
    common_params =  FilePathManager().GetFileAndCheckExist("config_file")
    camera_info_file = 'file://' + os.path.join(get_package_share_directory('yahboomcar_bringup'),'param','usb_camera_info.yaml')
    uasb_camera = Node(
        package='usb_cam',
        executable='usb_cam_node_exe',
        name='usb_cam',
        output='both',
        sigterm_timeout='15',
        sigkill_timeout='15',
        parameters=[common_params,
            {'video_device': '/dev/video0'},
            {'image_width': 640},
            {'image_height': 480},
            {'framerate': 30.0},
            {'camera_info_url': camera_info_file},
            {'enable_rectify': True}
        ],
        arguments=['--ros-args', '--log-level', LaunchConfiguration('log_level')],
    )

    ld.add_action(DeclareLaunchArgument('log_level', default_value='info',description='ros2 logging level'))
    ld.add_action(uasb_camera)
    return ld

• io_method: image acquisition method; mmap is memory mapping, which is more efficient

• frame_id: name of the camera TF coordinate frame, here camera

• pixel_format: pixel format conversion; yuyv2rgb converts the raw YUYV format to RGB

• av_device_format: raw device data format YUV422P

• brightness / contrast / saturation / sharpness / gain: brightness, contrast, saturation, sharpness, gain; -1 means use the camera default value

• auto_white_balance: enable automatic white balance

• white_balance: white balance color temperature 6000K (takes effect when automatic white balance is off)

• autoexposure: enable automatic exposure

• exposure: exposure value 80 (takes effect when automatic exposure is off)

• focus: focus value; -1 means use the camera default focus

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usb_cam:
    ros__parameters:
      io_method: "mmap"
      frame_id: "camera"
      pixel_format: "yuyv2rgb"
      av_device_format: "YUV422P"
      brightness: -1
      contrast: -1
      saturation: -1
      sharpness: -1
      gain: -1
      auto_white_balance: true
      white_balance: 6000
      autoexposure: true
      exposure: 80
      focus: -1

• Adjusting the exposure value of the USB monocular camera: as shown in the figure below, if the image is overexposed or too dark, you can turn off the camera's automatic exposure and manually adjust exposure