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v4l2_camera

A ROS 2 camera driver using Video4Linux2 (V4L2).

Installation

This article details how to build and run this package. It focuses on Raspberry Pi OS with the Raspberry Pi Camera Module V2 but should generalise for most systems.

Building from source

If you need to modify the code or ensure you have the latest update you will need to clone this repo then build the package.

$ git clone --branch galactic https://github.com/tier4/ros2_v4l2_camera.git
$ colcon build

Most users will also want to set up compressed transport using the dependencies below.

Usage

Publish camera images, using the default parameters:

    ros2 run v4l2_camera v4l2_camera_node

Preview the image (open another terminal):

    ros2 run rqt_image_view rqt_image_view

Dependencies

  • image_transport - makes it possible to set up compressed transport of the images, as described below.

    The ROS 2 port of image_transport in the image_common repository is needed inside of your workspace:

      git clone --branch ros2 https://github.com/ros-perception/image_common.git src/image_common

    Note that image_transport only supports raw transport by default and needs additional plugins to actually provide compression; see below how to do this.

Nodes

v4l2_camera_node

The v4l2_camera_node interfaces with standard V4L2 devices and publishes images as sensor_msgs/Image messages.

Published Topics

  • /image_raw - sensor_msgs/Image

    The image.

Parameters

  • video_device - string, default: "/dev/video0"

    The device the camera is on.

  • pixel_format - string, default: "YUYV"

    The pixel format to request from the camera. Must be a valid four character 'FOURCC' code supported by V4L2 and by your camera. The node outputs the available formats supported by your camera when started.
    Currently supported: "YUYV", "UYVY" or "GREY". ("UYVY" support is only available on systems with CUDA)

  • output_encoding - string, default: "rgb8"

    The encoding to use for the output image.
    Currently supported: "rgb8", "yuv422" or "mono8".

  • image_size - integer_array, default: [640, 480]

    Width and height of the image.

  • time_per_frame - integer_array, default: current device setting

    The time between two successive frames. The expected value is a ratio defined by an array of 2 integers. For instance, a value of [1, 30] sets a period of 1/30, and thus a framrate of 30Hz.

    If the provided period is not supported, the driver may choose another period near to it. In that case the parameter change is reported to have failed.

  • use_v4l2_buffer_timestamps - bool, default: true

    Flag to determine image timestamp behaviour. When true, the images will be timestamped according to the V4L2 buffer timestamps. When false the image timestamps will be the system time when the image buffer is read.

  • timestamp_offset - int64_t, default: 0

    Offset to be added to the image timestamp, in nanoseconds. This is useful to correct for delays in the image capture pipeline, when performing synchronization with other sensor data. Note that this value will usually be negative (correcting for delays rather than adding delay to the timestamp).

  • Camera Control Parameters

    Camera controls, such as brightness, contrast, white balance, etc, are automatically made available as parameters. The driver node enumerates all controls, and creates a parameter for each, with the corresponding value type. The parameter name is derived from the control name reported by the camera driver, made lower case, commas removed, and spaces replaced by underscores. So Brightness becomes brightness, and White Balance, Automatic becomes white_balance_automatic.

Compressed Transport

By default image_transport only supports raw transfer, plugins are required to enable compression. Standard ones are available in the image_transport_plugins repository. These depend on the OpenCV facilities provided by the vision_opencv repository. You can clone these into your workspace to get these:

cd path/to/workspace
git clone https://github.com/ros-perception/vision_opencv.git --branch ros2 src/vision_opencv
git clone https://github.com/ros-perception/image_transport_plugins.git --branch ros2 src/image_transport_plugins

Building: Ubuntu

The following packages are required to be able to build the plugins:

sudo apt install libtheora-dev libogg-dev libboost-python-dev

Building: Arch

To get the plugins compiled on Arch Linux, a few special steps are needed:

  • Arch provides OpenCV 4.x, but OpenCV 3.x is required

  • Arch provides VTK 8.2, but VTK 8.1 is required

  • boost-python is used, which needs to be linked to python libs explicitly:

      colcon build --symlink-install --packages-select cv_bridge --cmake-args "-DCMAKE_CXX_STANDARD_LIBRARIES=-lpython3.7m"

Usage

If the compression plugins are compiled and installed in the current workspace, they will be automatically used by the driver and an additional /image_raw/compressed topic will be available.

Neither Rviz2 or showimage use image_transport (yet). Therefore, to be able to view the compressed topic, it needs to be republished uncompressed. image_transport comes with the republish node to do this:

ros2 run image_transport republish compressed in/compressed:=image_raw/compressed raw out:=image_raw/uncompressed

The parameters mean:

  • compressed - the transport to use for input, in this case 'compressed'. Alternative: raw, to republish the raw /image_raw topic
  • in/compressed:=image_raw/compressed - by default, republish uses the topics in and out, or in/compressed for example if the input transport is 'compressed'. This parameter is a ROS remapping rule to map those names to the actual topic to use.
  • raw - the transport to use for output. If omitted, all available transports are provided.
  • out:=image_raw/uncompressed - remapping of the output topic.