Services

In this exercise, we will create a custom service by defining a .srv file. Then we will write server and client nodes to utilize this service.

Motivation

The first type of ROS communication that we explored was a one-way interaction called messages which are sent over channels called topics. Now we are going to explore a different communication type, which is a two-way interaction via a request from one node to another and a response from that node to the first. In this module we will create a service server (waits for request and comes up with response) and client (makes request for info then waits for response).

Further Information and Resources

Scan-N-Plan Application: Problem Statement

We now have a base ROS node which is subscribing to some information and we want to build on this node. In addition we want this node to serve as a sub-function to another “main” node. The original vision node will now be responsible for subscribing to the AR information and responding to requests from the main workcell node.

Your goal is to create a more intricate system of nodes:

  1. Update the vision node to include a service server
  2. Create a new node which will eventually run the Scan-N-Plan App
    • First, we’ll create the new node (myworkcell_core) with only a simple service client. We will later add more code to build up the full application control node.

Scan-N-Plan Application: Guidance

Create Service Definition

  1. Similar to the message file located in the fake_ar_publisher package, we need to create a service file. The following is a generic structure of a service file:

    #request
    ---
    #response
    
  2. Create a folder called srv inside your myworkcell_core package (at same level as the package’s src folder)

    cd ~/ros2_ws/src/myworkcell_core
    mkdir srv
    
  3. Create a file (gedit or QT) called LocalizePart.srv inside the srv folder.

  4. Inside the file, define the service as outlined above with a request of type string named base_frame and a response that has a geometry_msgs/Pose field named pose, and a boolean field named success:

    #request
    string base_frame
    ---
    #response
    geometry_msgs/Pose pose
    bool success
    
    • It is good practice to include a response field that explicitly indicates success or failure of the service call. Services often also include a string field that can provide a more detailed description of the error to the calling client.
  5. Edit the package’s CMakeLists.txt and package.xml to add dependencies on key packages:

    • The rosidl_default_generators package is required to build C++ code from the .srv file created in the previous step
    • The rosidl_default_runtime package provides runtime dependencies for new messages
    • geometry_msgs provides the Pose message type used in our service definition
    1. Edit the package’s CMakeLists.txt file to add the new build-time dependencies alongside the existing find_package rules:

      find_package(geometry_msgs REQUIRED)
      find_package(rosidl_default_generators REQUIRED)
      
    2. Edit the package.xml file to add the appropriate build/run dependencies:

      <build_depend>rosidl_default_generators</build_depend>
      <exec_depend>rosidl_default_runtime</exec_depend>
      <depend>geometry_msgs</depend>
      
    3. Also add a special tag that tells the ROS build system this package defines ROS interfaces.

      <member_of_group>rosidl_interface_packages</member_of_group>
      

      This is generally placed with the package metadata, before the dependencies.

  6. Edit the package’s CMakeLists.txt to add rules to generate the new service files:

    1. The following CMake function is invoked with the service file you created and creates the target to generate the interface-specific code:

      rosidl_generate_interfaces(${PROJECT_NAME}
        "srv/LocalizePart.srv"
        DEPENDENCIES geometry_msgs
      )
      
    2. Add the following line after the call to ament_target_dependencies for the the vision_node. This makes the vision_node target depend on the generated interface target so that the generated code can be used in the node:

      rosidl_target_interfaces(vision_node ${PROJECT_NAME} "rosidl_typesupport_cpp")
      
  7. Now you have a service defined in you package and you can attempt to build the code to generate the service:

    colcon build
    

Service Server

  1. Edit vision_node.cpp; remember that the ros documentation is a resource.

  2. Add the header for the service we just created

     #include <myworkcell_core/srv/localize_part.hpp>
    
    • _Note the slightly different naming convention used for the Service Definition (LocalizePart) and generated header file (localize_part.hpp).
  3. In the Localizer class, create a callback method named localizePart. Remember that your request and response types were defined in the LocalizePart.srv file. The arguments to the callback function are the request and response type, with the general structure of Package::ServiceName::Request::SharedPtr or Package::ServiceName::Response::SharedPtr.

    void localizePart(myworkcell_core::srv::LocalizePart::Request::SharedPtr req,
                      myworkcell_core::srv::LocalizePart::Response::SharedPtr res)
    {
    
    }
    
  4. Now add code to the localizePart callback function to fill in the Service Response. Eventually, this callback will transform the pose received from the fake_ar_publisher (in visionCallback) into the frame specifed in the Service Request. For now, we will skip the frame-transform, and just pass through the data received from fake_ar_publisher. Copy the pose measurement received from fake_ar_publisher (saved to last_msg_) directly to the Service Response.

    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;
        return;
      }
    
      res->pose = p->pose.pose;
      res->success = true;
    }
    
  5. Now we need to create the server object that interfaces between this callback function and other ROS nodes. Add a roscpp::Service member variable named server_ near the other Localizer class member variables:

    rclcpp::Service<myworkcell_core::srv::LocalizePart>::SharedPtr server_;
    
  6. In the Localizer class constructor, initialize the server object:

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

    Note the use of std::bind again to reference a callback function that is a method of a class object. The use of two std::placeholders arguments indicates the callback will have two arguments when it is called.

  7. You should also comment out the RCLCPP_INFO call in your visionCallback function, to avoid cluttering the screen with useless info.

  8. Build the updated vision_node, to make sure there are no compile errors. You may see a warning about unused Service::req input… this is expected, since we haven’t yet used the request data in our callback function.

Service Client

  1. Create a new node (inside the myworkcell_core/src directory), named myworkcell_node.cpp. This will eventually be our main “application node”, that controls the sequence of actions in our Scan & Plan task. The first action we’ll implement is to request the position of the AR target from the Vision Node’s LocalizePart service we created above.

  2. Be sure to include the standard ros header as well as the header for the LocalizePart service:

    #include <rclcpp/rclcpp.hpp>
    #include <myworkcell_core/srv/localize_part.hpp>
    
  3. Create a standard C++ main function, with typical ROS initialization:

    int main(int argc, char **argv)
    {
      // This must be called before anything else ROS-related
      rclcpp::init(argc, argv);
    
      rclcpp::shutdown();
      return 0;
    }
    
  4. Following best-practice guidance, we will create a new ScanNPlan class (derived from rclcpp::Node) to contain the functionality of our new node. Create a skeleton structure of this class, with an empty constructor and a private area for some internal/private variables.

    class ScanNPlan : public rclcpp::Node
    {
    public:
      ScanNPlan() : Node("scan_n_plan")
      {
    
      }
    
    private:
      // Planning components
    
    };
    
  5. Within your new ScanNPlan class, define a ROS Service Client as a private member variable of the class. This client object will allow us to connect to the vision node’s Service Server. Initialize the Client in the ScanNPlan constructor. Both the service type (in the variable declaration) and the service name (in the object constructor) should match what we set up in the vision_node server earlier.

    class ScanNPlan : public rclcpp::Node
    {
    public:
      ScanNPlan() : Node("scan_n_plan")
      {
        vision_client_ = this->create_client<myworkcell_core::srv::LocalizePart>("localize_part");
      }
    
    private:
      // Planning components
      rclcpp::Client<myworkcell_core::srv::LocalizePart>::SharedPtr vision_client_;
    };
    
  6. Create a void function within the ScanNPlan class named start, with no arguments. This will eventually contain most of our application workflow.

    class ScanNPlan : public rclcpp::Node
    {
    public:
      ...
    
      void start()
      {
        RCLCPP_INFO(get_logger(), "Attempting to localize part");
      }
      ...
    };
    
  7. When the node is first created, it takes a few seconds to connect to other nodes and detremine what services and topics are available. Attempting to call the service during this time may cause the call to hang indefinitely. Add a call to wait for the service to be available before submitting the request:

    class ScanNPlan : public rclcpp::Node
    {
      ...
      void start()
      {
        RCLCPP_INFO(get_logger(), "Attempting to localize part");
    
        // Wait for service to be available
        if (!vision_client_->wait_for_service(std::chrono::seconds(5))) {
          RCLCPP_ERROR(get_logger(), "Unable to find localize_part service. Start vision_node first.");
          return;
        }
      ...
    };
    
  8. Now add code to prepare the request data and call the service. For now, the request fields are left empty. They will be added in a later exercise.

    class ScanNPlan : public rclcpp::Node
    {
    public:
      ...
      void start()
      {
        RCLCPP_INFO(get_logger(), "Attempting to localize part");
    
        // Wait for service to be available
        if (!vision_client_->wait_for_service(std::chrono::seconds(5))) {
          RCLCPP_ERROR(get_logger(), "Unable to find localize_part service. Start vision_node first.");
          return;
        }
    
        // Create a request for the LocalizePart service call
        auto request = std::make_shared<myworkcell_core::srv::LocalizePart::Request>();
    
        auto future = vision_client_->async_send_request(request);
      }
      ...
    };
    

    The async_send_request function is used on the vision_client_ object to initiate the service call. Notice that it doesn’t return a response object, but instead, something called a future. This is because the function immediately returns after sending the request and does not wait for a response from the server. It is our responsibility to wait for the response to arrive, which will be known by the future object becoming ‘complete’.

  9. Now add the code that will wait until the service response arrives and then prints the response. This is a bit complex, because we are turning the asynchronous ROS2 service call into a synchronous blocking call.

    void start()
    {
      RCLCPP_INFO(get_logger(), "Attempting to localize part");
    
      // Wait for service to be available
      if (!vision_client_->wait_for_service(std::chrono::seconds(5))) {
        RCLCPP_ERROR(get_logger(), "Unable to find localize_part service. Start vision_node first.");
        return;
      }
    
      // Create a request for the LocalizePart service call
      auto request = std::make_shared<myworkcell_core::srv::LocalizePart::Request>();
    
      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");
        return;
      }
    
      auto response = future.get();
      if (! response->success)
      {
        RCLCPP_ERROR(this->get_logger(), "LocalizePart service failed");
        return;
      }
    
      RCLCPP_INFO(this->get_logger(), "Part Localized: x: %f, y: %f, z: %f",
          response->pose.position.x,
          response->pose.position.y,
          response->pose.position.z);
    }
    
    • Note that the waiting function is a form of spinning, the same as the rclcpp::spin function used in the vision_node. This spin function allows the backend ROS code to run, listening for the incoming service response and managing other node-maintenance tasks.
    • Important: You can trigger deadlocks if you call ros “spin” functions simultaneously in multiple places. For example, you may need a more complex “spin” design if you are attempting to wait for a service response inside a subscriber’s callback function. There are ways around this limitation but it is beyond the scope of this material.
    • An alternative to the synchronous wait shown above is to provide a callback function along with the service request. For some applications, this asynchronous design might make more sense.
  10. Now back in myworkcell_node’s main function, instantiate an object of the ScanNPlan class and call the object’s start function.

    // Create the ScanNPlan node
    auto app = std::make_shared<ScanNPlan>();
    app->start();
    
  11. Edit the package’s CMakeLists.txt to build the new node (executable), with its associated dependencies. Add the following rules to the appropriate sections, directly under the matching rules for vision_node:

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

    Be sure to remove the PUBLIC keyword from ament_target_dependencies(). It conflicts with other CMake calls made under the hood. Also add myworkcell_node to the existing call to install along with vision_node:

    install(TARGETS vision_node myworkcell_node
        ...
    )
    
  12. Build the nodes to check for any compile-time errors:

    colcon build
    

Use New Service

  1. Enter each of these commands in their own terminal:

    ros2 run fake_ar_publisher fake_ar_publisher_node
    ros2 run myworkcell_core vision_node
    ros2 run myworkcell_core myworkcell_node
    
    • If you get errors that the ros2 commands can’t find certain shared objects or executables, try re-sourcing the setup file (source ~/ros2_ws/install/setup.bash). This is required since we added a new service-definition and a new node.
    • The values reported by the localization service should match the values published by the fake_ar_publisher node that you observed earlier (through ros2 topic echo or rqt_plot).