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Zivid ROS driver

This is the official ROS driver for Zivid 3D cameras.

Build Status Zivid Image


Contents: Installation | Getting Started | Launching | Services | Topics | Configuration | Samples | FAQ


Installation

ROS

This driver supports Ubuntu 16.04 with ROS Kinetic, Ubuntu 18.04 with ROS Melodic and Ubuntu 20.04 with ROS Noetic. Follow the official ROS installation instructions for your OS.

Also install catkin and git:

Ubuntu 16.04/18.04:

sudo apt-get update
sudo apt-get install -y python-catkin-tools git

Ubuntu 20.04:

sudo apt-get update
sudo apt-get install -y python3-catkin-tools python3-osrf-pycommon git

Zivid SDK

To use the ROS driver you need to download and install the "Zivid Core" package. Zivid SDK version 2.5 is supported. See releases for older ROS driver releases that supports older SDK versions.

Follow this guide to install "Zivid Core" for your version of Ubuntu. The "Zivid Studio" and "Zivid Tools" packages can be useful to test your system setup and camera, but are not required by the driver.

An OpenCL 1.2 compatible GPU with driver installed is required by the SDK. Follow this guide to install OpenCL drivers for your system.

C++ compiler

A C++17 compiler is required.

Ubuntu 16.04:

sudo apt-get install -y software-properties-common
sudo add-apt-repository -y ppa:ubuntu-toolchain-r/test
sudo apt-get update
sudo apt-get install -y g++-8

Ubuntu 18.04/20.04:

sudo apt-get install -y g++

Downloading and building Zivid ROS driver

First, load the setup.bash script into the current session.

Ubuntu 16.04:

source /opt/ros/kinetic/setup.bash

Ubuntu 18.04:

source /opt/ros/melodic/setup.bash

Ubuntu 20.04:

source /opt/ros/noetic/setup.bash

Create the workspace and src directory:

mkdir -p ~/catkin_ws/src

Clone the Zivid ROS project into the src directory:

cd ~/catkin_ws/src
git clone https://github.com/zivid/zivid-ros.git

Install dependencies:

cd ~/catkin_ws
sudo apt-get update
rosdep update
rosdep install --from-paths src --ignore-src -r -y

Finally, build the driver.

Ubuntu 16.04:

catkin build -DCMAKE_CXX_COMPILER=/usr/bin/g++-8

Ubuntu 18.04/20.04:

catkin build

Getting started

Connect the Zivid camera to your USB3 port on your PC. You can use the ZividListCameras command-line tool available in the "Zivid Tools" package to confirm that your system has been configured correctly, and that the camera is discovered by your PC. You can also open Zivid Studio and connect to the camera. Close Zivid Studio before continuing with the rest of this guide.

Launch sample_capture_assistant.py to test that everything is working:

cd ~/catkin_ws && source devel/setup.bash
roslaunch zivid_samples sample.launch type:=sample_capture_assistant.py

This will start the zivid_camera driver node, the sample_capture_assistant.py node, as well as rviz to visualize the point cloud and the 2D color and depth images and rqt_reconfigure to view or change capture settings.

The sample_capture_assistant.py node will first call the capture_assistant/suggest_settings service to find suggested capture settings for your particular scene, then call the capture service to capture using those settings. If everything is working, the point cloud, color image and depth image should be visible in rviz.

You can adjust the maximum capture time by changing variable max_capture_time in sample_capture_assistant.py and re-launching the sample.

A more detailed description of the zivid_camera driver follows below.

For sample code in C++ and Python, see the Samples section.

Launching the driver

It is required to specify a namespace when starting the driver. All the services, topics and configurations will be pushed into this namespace.

To launch the driver, first start roscore in a seperate terminal window:

roscore

In another terminal run:

cd ~/catkin_ws && source devel/setup.bash

Then, launch the driver either as a node or a nodelet. To launch as a node:

ROS_NAMESPACE=zivid_camera rosrun zivid_camera zivid_camera_node

To launch as a nodelet:

ROS_NAMESPACE=zivid_camera rosrun nodelet nodelet standalone zivid_camera/nodelet

Launch Parameters (advanced)

The following parameters can be specified when starting the driver. Note that all the parameters are optional, and typically not required to set.

For example, to launch the driver with frame_id specified, append _frame_id:=camera1 to the rosrun command:

ROS_NAMESPACE=zivid_camera rosrun zivid_camera zivid_camera_node _frame_id:=camera1

settings_file_path (string, default: "")

Specify the path to a settings .yml file. If specified, this file is used to construct the Zivid Settings and apply them at start up. All calls to the capture service will be made using these settings, unless they are change via e.g. the capture_assistant/suggest_settings service.

file_camera_path (string, default: "")

Specify the path to a file camera to use instead of a real Zivid camera. This can be used to develop without access to hardware. The file camera returns the same point cloud for every capture. Click here to download a file camera.

frame_id (string, default: "zivid_optical_frame")

Specify the frame_id used for all published images and point clouds.

max_capture_acquisitions (int, default: 10)

Specify the number of dynamic_reconfigure settings/acquisition_<n> nodes that are created. This number defines the maximum number of acquisitions that can be a part of a 3D capture. All settings/acquisition_<n> nodes are by default enabled=false (see section Configuration). If you need to perform 3D HDR capture with more than 10 enabled acquisitions then increase this number. Otherwise it can be left as default. We do not recommend lowering this setting, especially if you are using the capture_assistant/suggest_settings service.

serial_number (string, default: "")

Specify the serial number of the Zivid camera to use. Important: When passing this value via the command line or rosparam the serial number must be prefixed with a colon (:12345). This parameter is optional. By default the driver will connect to the first available camera.

Services

capture_assistant/suggest_settings

zivid_camera/CaptureAssistantSuggestSettings.srv

Invoke this service to analyze your scene and find suggested settings for your particular scene, camera distance, ambient lighting conditions, etc. The suggested settings are configured on this node and accessible via dynamic_reconfigure, see section Configuration. When this service has returned you can invoke the capture service to trigger a 3D capture using these suggested settings.

This service has two parameters:

max_capture_time (duration):

Specify the maximum capture time for the settings suggested by the Capture Assistant. A longer capture time may be required to get good data for more challenging scenes. Minimum value is 0.2 sec and maximum value is 10.0 sec.

ambient_light_frequency (uint8):

Possible values are: AMBIENT_LIGHT_FREQUENCY_NONE, AMBIENT_LIGHT_FREQUENCY_50HZ, AMBIENT_LIGHT_FREQUENCY_60HZ. Can be used to ensure that the suggested settings are compatible with the frequency of the ambient light in the scene. If ambient light is unproblematic, use AMBIENT_LIGHT_FREQUENCY_NONE for optimal performance. Default is AMBIENT_LIGHT_FREQUENCY_NONE.

See Sample Capture Assistant for code example.

capture

zivid_camera/Capture.srv

Invoke this service to trigger a 3D capture. See section Configuration for how to configure the 3D capture settings. The resulting point cloud is published on topics points/xyz and points/xyzrgba, color image is published on topic color/image_color, and depth image is published on topic depth/image. Camera calibration is published on topics color/camera_info and depth/camera_info.

See Sample Capture for code example.

capture_2d

zivid_camera/Capture2D.srv

Invoke this service to trigger a 2D capture. See section Configuration for how to configure the 2D capture settings. The resulting 2D image is published to topic color/image_color. Note: 2D RGB image is also published as a part of 3D capture, see capture.

See Sample Capture 2D for code example.

camera_info/model_name

zivid_camera/CameraInfoModelName.srv

Returns the camera's model name.

camera_info/serial_number

zivid_camera/CameraInfoSerialNumber.srv

Returns the camera's serial number.

is_connected

zivid_camera/IsConnected.srv

Returns if the camera is currently in Connected state (from the perspective of the ROS driver). The connection status is updated by the driver every 10 seconds and before each capture service call. If the camera is not in Connected state the driver will attempt to re-connect to the camera when it detects that the camera is available. This can happen if the camera is power-cycled or the USB cable is unplugged and then replugged.

load_settings

zivid_camera/LoadSettings.srv

Loads settings from a .yml file and applies them to the Zivid Camera.

Topics

The Zivid ROS driver provides several topics providing 3D, color, SNR and camera calibration data as a result of calling capture and/or capture_2d. The different output topics provides flexibility for different use cases. Note that for performance reasons no messages are generated or sent on topics with zero active subscribers.

color/camera_info

sensor_msgs/CameraInfo

Camera calibration and metadata.

color/image_color

sensor_msgs/Image

Color/RGBA image. RGBA image is published as a result of invoking the capture or capture_2d service. Images are encoded as "rgba8", where the alpha channel is always 255.

depth/camera_info

sensor_msgs/CameraInfo

Camera calibration and metadata.

depth/image

sensor_msgs/Image

Depth image. Each pixel contains the z-value (along the camera Z axis) in meters. The image is encoded as 32-bit float. Pixels where z-value is missing are NaN.

points/xyzrgba

sensor_msgs/PointCloud2

Point cloud data. Sent as a result of the capture service. The output is in the camera's optical frame, where x is right, y is down and z is forward. The included point fields are x, y, z (in meters) and rgba (color).

points/xyz

sensor_msgs/PointCloud2

Point cloud data. This topic is similar to topic points/xyzrgba, except that only the XYZ 3D coordinates are included. This topic is recommended if you don't need the RGBA values.

snr/camera_info

sensor_msgs/CameraInfo

Camera calibration and metadata.

snr/image

sensor_msgs/Image

Each pixel contains the SNR (signal-to-noise ratio) value. The image is encoded as 32-bit float. Published as a part of the capture service.

normals/xyz

sensor_msgs/PointCloud2

Normals for the point cloud. The included fields are normal x, y and z coordinates. Each coordinate is a float value. There are no additional padding floats, so point-step is 12 bytes (3*4 bytes). The normals are unit vectors. Note that subscribing to this topic will cause some additional processing time for calculating the normals.

Configuration

The zivid_camera node supports both single-acquisition (2D and 3D) and multi-acquisition HDR captures (3D only). 3D HDR-capture works by taking several acquisitions with different settings (for example different exposure time) and combining them into one high-quality point cloud. For more information about HDR capture, visit our knowledge base.

The capture settings available in the zivid_camera node matches the settings in the Zivid API. To become more familiar with the different settings and what they do, see the API reference for the Settings and Settings2D classes, or use Zivid Studio.

The settings can be viewed and configured using dynamic_reconfigure. Use rqt_reconfigure to view/change the settings using a GUI:

rosrun rqt_reconfigure rqt_reconfigure

If you want to experiment with the capture settings, launch the Sample Capture sample, which will capture in a loop forever, and use rqt_reconfigure to adjust the settings.

The available capture settings are organized into a hierarchy of configuration nodes. 3D settings are available under the /settings namespace, while 2D settings are available under /settings_2d.

/settings
    ...
    /acquisition_0
        ...
    /acquisition_1
        ...
    ...
    /acquisition_9
        ...
/settings_2d
    ...
    /acquisition_0
        ...

Important notice for C++ users: The default value and min/max values of the settings are dependent on what Zivid camera model you are using. Therefore you need to query the server for the correct values after you have connected to the camera. To initialize a settings Config object you should not use the static __getDefault()__ methods of the auto-generated C++ config classes (zivid_camera::SettingsConfig, zivid_camera::SettingsAcquisitionConfig, zivid_camera::Settings2DConfig, and zivid_camera::Settings2DAcquisitionConfig). Instead, you should query the server for the default values using dynamic_reconfigure::Client<T>::getDefaultConfiguration(). See the C++ samples for how to do this. For Python users this is already handled by dynamic_reconfigure.client.Client.

Note: The Capture Assistant feature can be used to find optimized 3D capture settings for your scene. Refer to service capture_assistant/suggest_settings.

3D Settings

Acquisition settings

settings/acquisition_<n>/ contains settings for an individual acquisition. By default <n> can be 0 to 9 for a total of 10 acquisitions. The total number of acquisitions can be configured using the launch parameter max_capture_acquisitions (see section Launch Parameters above).

settings/acquisition_<n>/enabled controls if acquisition <n> will be included when the capture service is invoked. If only one acquisition is enabled the capture service performs a 3D single-capture. If more than one acquisition is enabled the capture service will perform a 3D HDR-capture. By default enabled is false. In order to capture a point cloud at least one acquisition needs to be enabled.

Name Type Zivid API Setting Note
settings/acquisition_<n>/enabled bool
settings/acquisition_<n>/aperture double Settings::Acquisition::Aperture
settings/acquisition_<n>/brightness double Settings::Acquisition::Brightness
settings/acquisition_<n>/exposure_time int Settings::Acquisition::ExposureTime Microseconds
settings/acquisition_<n>/gain double Settings::Acquisition::Gain

Processing settings

settings/ contains settings related to processing, like color balance and filter settings.

Name Type Zivid API Setting
settings/processing_color_balance_blue double Settings::Processing::Color::Balance::Blue
settings/processing_color_balance_green double Settings::Processing::Color::Balance::Green
settings/processing_color_balance_red double Settings::Processing::Color::Balance::Red
settings/processing_color_gamma double Settings::Processing::Color::Gamma
settings/processing_filters_noise_removal_enabled bool Settings::Processing::Filters::Noise::Removal::Enabled
settings/processing_filters_noise_removal_threshold double Settings::Processing::Filters::Noise::Removal::Threshold
settings/processing_filters_outlier_removal_enabled bool Settings::Processing::Filters::Outlier::Removal::Enabled
settings/processing_filters_outlier_removal_threshold double Settings::Processing::Filters::Outlier::Removal::Threshold
settings/processing_filters_reflection_removal_enabled bool Settings::Processing::Filters::Reflection::Removal::Enabled
settings/processing_filters_smoothing_gaussian_enabled bool Settings::Processing::Filters::Smoothing::Gaussian::Enabled
settings/processing_filters_smoothing_gaussian_sigma double Settings::Processing::Filters::Smoothing::Gaussian::Sigma

Experimental settings

Note that these settings may be changed, renamed or removed in future SDK releases.

Name Type Zivid API Setting
settings/experimental_engine enum Settings::Experimental::Engine
settings/processing_color_experimental_tone_mapping_enabled enum Settings::Processing::Color::Experimental::ToneMapping::Enabled
settings/processing_filters_experimental_contrast_distortion_correction_enabled bool Settings::Processing::Filters::Experimental::ContrastDistortion::Correction::Enabled
settings/processing_filters_experimental_contrast_distortion_correction_strength double Settings::Processing::Filters::Experimental::ContrastDistortion::Correction::Strength
settings/processing_filters_experimental_contrast_distortion_removal_enabled bool Settings::Processing::Filters::Experimental::ContrastDistortion::Removal::Enabled
settings/processing_filters_experimental_contrast_distortion_removal_threshold double Settings::Processing::Filters::Experimental::ContrastDistortion::Removal::Threshold

2D settings

Acquisition settings

To trigger a 2D capture, invoke the capture_2d service. Note that settings_2d/acquisition_0/enabled is default false, and must be set to true before calling the capture_2d service, otherwise the service will return an error.

Name Type Zivid API Setting Note
settings_2d/acquisition_0/enabled bool
settings_2d/acquisition_0/aperture double Settings2D::Acquisition::Aperture
settings_2d/acquisition_0/brightness double Settings2D::Acquisition::Brightness
settings_2d/acquisition_0/exposure_time int Settings2D::Acquisition::ExposureTime Microseconds
settings_2d/acquisition_0/gain double Settings2D::Acquisition::Gain

Processing settings

settings_2d/ contains settings related to processing of the captured image.

Name Type Zivid API Setting
settings_2d/processing_color_balance_blue double Settings2D::Processing::Color::Balance::Blue
settings_2d/processing_color_balance_green double Settings2D::Processing::Color::Balance::Green
settings_2d/processing_color_balance_red double Settings2D::Processing::Color::Balance::Red
settings_2d/processing_color_gamma double Settings2D::Processing::Color::Gamma

Samples

In the zivid_samples package we have added samples in C++ and Python that demonstrate how to use the Zivid ROS driver. These samples can be used as a starting point for your project.

Sample Capture Assistant

This sample shows how to use the Capture Assistant to capture with suggested settings for your particular scene. This sample first calls the capture_assistant/suggest_settings service to get the suggested settings. It then calls the capture service to invoke the 3D capture using those settings.

Source code: C++, Python

Using roslaunch (also launches roscore, zivid_camera, rviz and rqt_reconfigure):

roslaunch zivid_samples sample.launch type:=sample_capture_assistant_cpp
roslaunch zivid_samples sample.launch type:=sample_capture_assistant.py

Using rosrun (when roscore and zivid_camera are running):

rosrun zivid_samples sample_capture_assistant_cpp
rosrun zivid_samples sample_capture_assistant.py

Sample Capture

This sample performs single-acquisition 3D captures repeatedly. This sample shows how to configure the capture settings, how to subscribe to the points/xyzrgba topic, and how to invoke the capture service.

Source code: C++, Python

Using roslaunch (also launches roscore, zivid_camera, rviz and rqt_reconfigure):

roslaunch zivid_samples sample.launch type:=sample_capture_cpp
roslaunch zivid_samples sample.launch type:=sample_capture.py

Using rosrun (when roscore and zivid_camera are running):

rosrun zivid_samples sample_capture_cpp
rosrun zivid_samples sample_capture.py

Sample Capture 2D

This sample performs 2D captures repeatedly. This sample shows how to configure the 2D capture settings, how to subscribe to the color/image_color topic, and how to invoke the capture_2d service.

Source code: C++, Python

Using roslaunch (also launches roscore, zivid_camera, rviz and rqt_reconfigure):

roslaunch zivid_samples sample.launch type:=sample_capture_2d_cpp
roslaunch zivid_samples sample.launch type:=sample_capture_2d.py

Using rosrun (when roscore and zivid_camera are running):

rosrun zivid_samples sample_capture_2d_cpp
rosrun zivid_samples sample_capture_2d.py

Frequently Asked Questions

How to visualize the output from the camera in rviz

ROS_NAMESPACE=zivid_camera roslaunch zivid_camera visualize.launch

How to use multiple cameras

You can use multiple Zivid cameras simultaneously by starting one node per camera and specifying unique namespaces per node:

ROS_NAMESPACE=camera1 rosrun zivid_camera zivid_camera_node
ROS_NAMESPACE=camera2 rosrun zivid_camera zivid_camera_node

By default the zivid_camera node will connect to the first available/unused camera. We recommend that you first start the first node, wait for it to be ready (for example, by waiting for the capture service to be available), then start the second node. This avoids any race conditions where both nodes may try to connect to the same camera at the same time.

How to run the unit and module tests

This project comes with a set of unit and module tests to verify the provided functionality. To run the tests locally, first download and install the file camera used for testing:

wget -q https://www.zivid.com/software/FileCameraZividOne.zip
unzip ./FileCameraZividOne.zip
rm ./FileCameraZividOne.zip
sudo mkdir -p /usr/share/Zivid/data/
sudo mv ./FileCameraZividOne.zfc /usr/share/Zivid/data/

Then run the tests:

cd ~/catkin_ws && source devel/setup.bash
catkin run_tests && catkin_test_results ~/catkin_ws

The tests can also be run via docker. See the GitHub Actions configuration file for details.

How to enable debug logging

The node logs extra information at log level debug, including the settings used when capturing. Enable debug logging to troubleshoot issues.

rosconsole set /<namespace>/zivid_camera ros.zivid_camera debug

For example, if ROS_NAMESPACE=zivid_camera,

rosconsole set /zivid_camera/zivid_camera ros.zivid_camera debug

How to compile the project with warnings enabled

catkin build -DCOMPILER_WARNINGS=ON

License

This project is licensed under BSD 3-clause license, see the LICENSE file for details.

Support

Please report any issues or feature requests related to the ROS driver in the issue tracker. Visit Zivid Knowledge Base for general help on using Zivid 3D cameras. If you cannot find a solution to your issue, please contact customersuccess@zivid.com.

Acknowledgements

This FTP (Focused Technical Project) has received funding from the European Union's Horizon 2020 research and innovation programme under the project ROSIN with the grant agreement No 732287. For more information, visit rosin-project.eu.

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