ROS1 to ROS2 porting


Our goal for this exercise is to have you fully port a small ROS1 application into ROS2. We’ll be using the basic training material from sessions 1 and 2 as the initial ROS1 application. This will provide some exposure to the differences in the basic tools of ROS development including publishers, subscribers, services, and parameters. We will be using exercise 2.3 as the starting point.

Workspace setup

  1. Clone the ROS2 version of fake_ar_publisher into your ROS2 workspace

    cd ~/ros2_ws/src/
    git clone -b ros2
  2. Create empty ROS2 packages.

    cd ~/ros2_ws/src/
    ros2 pkg create myworkcell_core
    ros2 pkg create myworkcell_support
  3. Verify the workspace builds with colcon build

  4. Set up a new project in Qt Creator with ‘Build System’ set to ‘Colcon’ and ‘Distribution’ set to ‘/opt/ros/dashing’. This is optional but highly recommended since you will get code autocompletion when editing C++ in the Qt Creator IDE. Verify that the workspace builds successfully from inside the IDE.

  5. Copy the ROS1 code from the packages at ~/industrial_training/exercises/2.3/src/ into the empty ROS2 packages. We’ll want everything copied over except CMakeLists.txt and package.xml, where we will be modifying the empty ROS2 versions instead. For more complex porting efforts, it will likely be more efficient to directly modify the ROS1 versions of these files.


We will more or less follow the same sequence that the ROS1 basic training takes in switching to ROS2.

Topic subscription

  1. Open and start editing the CMakeLists.txt file in myworkcell_core

  2. Package dependencies: Ament packages you depend on are now found directly using the CMake find_package command. Almost always the first invocation will be find_package(ament_cmake) which is required to make this package an ament package.

    Add additional dependencies for this application below this first find_package command:

    find_package(rclcpp REQUIRED)
    find_package(fake_ar_publisher_msgs REQUIRED)
  3. Build the vision node: An executable is added in the usual CMake way. Rather than use include_directories and target_link_libraries to depend on other packages, a convenience macro is provided to depend on other ament packages.

    add_executable(vision_node src/vision_node.cpp)
    ament_target_dependencies(vision_node rclcpp fake_ar_publisher)
  4. Install the vision node: Everything in ROS2 must have an install rule in order to be used at runtime.

    install(TARGETS vision_node
  5. Above the final call to ament_package() add a line which indicates which ament packages this package depends on at runtime:

    ament_export_dependencies(rclcpp fake_ar_publisher)
  6. You may try to build the workspace again now and you should get a compile error about ros/ros.h not being found. We’re now ready to port the C++ code. Open vision_node.cpp for editing.

  7. Change the headers: ROS2 requires headers to end in .hpp instead of .h and includes for msgs and srv require the file name to file/msg/ and file/srv/ respectively in their names.

    - #include <ros/ros.h>
    + #include <rclcpp/rclcpp.hpp>
    - #include <fake_ar_publisher/ARMarker.h>
    + #include <fake_ar_publisher/msg/ar_marker.hpp>
  8. Comment out the callbacks, the member variables, and the contents of the constructor. Change the Localizer class to inherit from rclcpp::Node.

    class Localizer : public rclcpp::Node
        : Node("vision_node")
  9. The main function can now be replaced with ROS2 equivalents of creating a node and spinning to wait for callbacks to be invoked:

    int main(int argc, char* argv[])
        // This must be called before anything else ROS-related
        rclcpp::init(argc, argv);
        // Create the node
        auto node = std::make_shared<Localizer>();
        // Don't exit the program.
  10. Now we’ll port the subscriber Replace the ar_sub_ and last_msg_ member variables with:

    rclcpp::Subscription<fake_ar_publisher::msg::ARMarker>::SharedPtr ar_sub_;
    fake_ar_publisher::msg::ARMarker::SharedPtr last_msg_;
  11. Add the subscription creation to the constructor:

    using namespace std::placeholders;
    ar_sub_ = this->create_subscription<fake_ar_publisher::msg::ARMarker>("ar_pose_marker", rclcpp::QoS(1),
      std::bind(&Localizer::visionCallback, this, _1));

    and the callback that stores the message:

    void visionCallback(fake_ar_publisher::msg::ARMarker::SharedPtr msg)
      last_msg_ = msg;
      RCLCPP_INFO(this->get_logger(), "Received ARMarker message");
  12. Verify the workspace builds now and test the topic subscription. Run the publisher node and vision node in separate terminals:

    ros2 run fake_ar_publisher fake_ar_publisher
    ros2 run myworkcell_core vision_node

Interface generation

We’ll now build the LocalizePart service type to use in the myworkcell_core package.

  1. The .srv file syntax is basically unchanged, but we do have to modify the definition. Since ROS2 does not allow you to return a boolean from a service callback, we must track success and failure ourselves. Add a success member to the response in LocalizePart.srv:

    string base_frame
    bool success
    geometry_msgs/Pose pose
  2. Modify CMake and package.xml to build the service. In CMakeLists.txt add additional dependencies and a call to generate custom interfaces:

    find_package(rosidl_default_generators REQUIRED)
    find_package(geometry_msgs REQUIRED)
      DEPENDENCIES geometry_msgs

    To use generated interfaces in the same package, another dependency must be added on built targets:

    rosidl_target_interfaces(vision_node ${PROJECT_NAME} "rosidl_typesupport_cpp")

    In package.xml make sure the format version is 3 and add the following tags:

  3. Make sure the workspace builds and you can now see the myworkcell_core/srv/LocalizePart service when running ros2 srv list.


  1. At the top of vision_node.cpp add/uncomment:

    #include <myworkcell_core/srv/localize_part.hpp>

    Then add the service server to the vision node, replacing the ServiceServer member variable with:

    rclcpp::Service<myworkcell_core::srv::LocalizePart>::SharedPtr server_;

    Add the service creation to the constructor:

    server_ = this->create_service<myworkcell_core::srv::LocalizePart>("localize_part",
      std::bind(&Localizer::localizePart, this, _1, _2));

    and the service callback:

    void localizePart(myworkcell_core::srv::LocalizePart::Request::SharedPtr req,
                      myworkcell_core::srv::LocalizePart::Response::SharedPtr res)
      // Read last message
      fake_ar_publisher::msg::ARMarker::SharedPtr p = last_msg_;
      if (!p){
        RCLCPP_ERROR(this->get_logger(), "no data");
        res->success = false;
      res->success = true;
      res->pose = p->pose.pose;
  2. Run both the fake_ar_publisher node and the vision_node and try manually calling the service.

  3. Now we’ll set up the application node to call the service. Add a new target to CMakeLists.txt:

    add_executable(myworkcell_node src/myworkcell_node.cpp)
    ament_target_dependencies(myworkcell_node rclcpp fake_ar_publisher_msgs)
    rosidl_target_interfaces(myworkcell_node ${PROJECT_NAME} "rosidl_typesupport_cpp")

    and add myworkcell_node to the existing install function call, after vision_node.

  4. Open myworkcell_node.cpp to start porting it over. As done with the vision node, convert the ScanNPlan class to inherit from rclcpp::Node and rewrite the main function in the same way. For now, comment out the code that loads the ‘base_frame’ parameter and call the start function with a hardcoded "world".

    class ScanNPlan : public rclcpp::Node
        ScanNPlan() : Node("scan_n_plan")
    int main(int argc, char* argv[])
  5. Replace the vision_client member variable with:

    rclcpp::Client<myworkcell_core::srv::LocalizePart>::SharedPtr vision_client_;

    and create it in the constuctor with:

    vision_client_ = this->create_client<myworkcell_core::srv::LocalizePart>("localize_part");
  6. The start function will be fully replaced since it is quite a bit more complex. Since ROS2 services are now asynchronous, the client returns a future object when called and the developer is responsible for spinning until a response returns from the vision node. Read through the new start function here before replacing to make sure you understand everything that is happening.

    void start(const std::string& base_frame)
        using namespace std::chrono_literals;
        // Need to wait until vision node has data
        RCLCPP_INFO(this->get_logger(), "Attempting to localize part in frame: %s", base_frame.c_str());
        // The vision client needs to wait until the service appears
        while (!vision_client_->wait_for_service(500ms)) {
            if (!rclcpp::ok()) {
                RCLCPP_ERROR(this->get_logger(), "client interrupted while waiting for service to appear.");
            RCLCPP_INFO(this->get_logger(), "waiting for service to appear...");
        // Create a request for the LocalizePart service call
        auto request = std::make_shared<myworkcell_core::srv::LocalizePart::Request>();
        // The base_frame that is passed in is used to fill the request
        request->base_frame = base_frame;
        auto future = vision_client_->async_send_request(request);
        if (rclcpp::spin_until_future_complete(this->get_node_base_interface(), future) != rclcpp::executor::FutureReturnCode::SUCCESS)
            RCLCPP_ERROR(this->get_logger(), "Failed to receive LocalizePart service response");
        auto result = future.get();
        if (! result->success)
            RCLCPP_ERROR(this->get_logger(), "LocalizePart service failed");
        RCLCPP_INFO(this->get_logger(), "Part Localized:  w: %f, x: %f, y: %f, z: %f",
  7. Verify everything builds and works


  1. Parameters work slightly differently than in ROS1. The most significant change is the parameter declaration mechanism, which, when given a default value, ensures that a parameter will exist under the given name which matches the type of the default. Modify the main function to declare and get the base_frame parameter:

    auto node = std::make_shared<ScanNPlan>();
    // String to store the base_frame parameter after getting it from the Node's parameter client
    std::string base_frame;
    node->declare_parameter("base_frame", "");
    node->get_parameter("base_frame", base_frame);
    if (base_frame.empty())
        RCLCPP_ERROR(node->get_logger(), "No 'base_frame' parameter provided");
        return -1;
    // Call the vision client's LocalizePart service using base_frame as a parameter
  2. Unfortunately, parameters can not currently be set on the command line when using ros2 run. To test that the parameter is set, you must create and save a YAML file:

        base_frame: world

    Then load this file when running the node:

    ros2 run myworkcell_core myworkcell_node __params:=my_params_file.yaml

Launch file

  1. Currently, the myworkcell_support package only contains a launch file for starting the three required nodes. We will port it to a ROS2 python launch script.

  2. Start by creating a new file under the launch/ directory.

  3. Modify the contents to add the required python imports and the required function which will return the launch configuration description:

    from launch import LaunchDescription
    import launch_ros.actions
    def generate_launch_description():
        print('Workcell is launching...')
  4. Each node in the XML launch file will correspond to a Node launch ‘action’ in the new launch description. The named arguments used in the action constructor should have clear meaning. You’ll need one for the fake_ar_publisher:

    fake_ar_pub_node = launch_ros.actions.Node(
        parameters=[{'x': -0.6},
                    {'y': 0.4},
                    {'z': 0.1},
                    {'camera_frame': 'camera_frame'}],

    one for the vision_node:

    vision_node = launch_ros.actions.Node(

    and one for myworkcell_node:

    myworkcell_node = launch_ros.actions.Node(
        parameters=[{'base_frame': 'world'}],

    Notice the parameters argument must be set with a list of dictionaries. Another common argument not used here is arguments, set with a list of command line arguments that the executable will start with.

  5. Now bundle the three nodes in a LaunchDescription and return it from the function:

    return LaunchDescription([fake_ar_pub_node, vision_node, myworkcell_node])
  6. Add an install call to CMakesList.txt to install the launch file:

    install(DIRECTORY launch
  7. Modify package.xml to show the runtime dependency on the packages

  8. After building the workspace test the launch file with:

    ros2 launch myworkcell_support

    Note that the file loaded by ros2 launch resides in the install/ directory and will not update if you edit the version in the src/ space. To avoid having to rebuild the workspace to see changes in the launch script, you can run colcon build with the --symlink-install option so the file in the install space is just a link back to the source space. This build option is also useful when developing ROS python code in general.