v4l2_camera

A ROS 2 camera driver using Video4Linux2 (V4L2). This repoistory was cloned from https://gitlab.com/boldhearts/ros2_v4l2_camera

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.

ROS package install

This is available from the ROS package repositories and can therefore be installed with the following command and your ROS version name:

apt-get install ros-<ros_version>-v4l2-camera

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 foxy https://gitlab.com/boldhearts/ros2_v4l2_camera.git src/v4l2_camera
$ 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

• /raw_image - 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" or "GREY"

• 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.

• 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.