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MicroROS-Pi5📖
01. Introduction
  • 0.Unpacking and reviewing video
  • 1. ReadMe - learning route
  • 2. Introduction to lidar
  • 3. Introduction to microROS control board
  • 4. FAQ
  • 5. About charging
02. Assembly course
  • Assembly steps
03. Preparation
  • First Trial
  • 1. Write firmware
  • 2. MicroROS control board parameter configuration
  • 3. Connect to MicroROS agent
  • 4. Connect to WIFI in hotspot mode
04. Quick start control course
  • 1. Self start handle control
  • 2. Close the self-starting handle control process
  • 3. Quick start keyboard control
  • 4. Map navigation and APP control
05. Robot basic course
  • 1. Robot information release
  • 2. Robot keyboard control
  • 3. Robot handle control
  • 4. Robot state estimation
  • 5. Linear speed calibration
  • 6. Angular velocity calibration
  • 7. Robot URDF model
06. ROS+OpenCV course
  • 1. Getting started with Opencv CV
  • 2. Geometric transformation
  • 3. Image processing and drawing
  • 4. Open Source CV image beautification
  • 5. QR code creation and recognition
  • 6. AR vision
  • 7. ROS+Opencv application
07. Mediapipe course
  • 1. Hand detection
  • 2. Posture detection
  • 3. Overall detection
  • 4. Face detection
  • 5. Face recognition
  • 6. Face effects
  • 7. 3D object recognition
  • 8. Brush
  • 9. Finger control
  • 10 .Gesture recognition
08. Robot visual interaction
  • 1. Monocular camera calibration
  • 2. Color tracking
  • 3. Object recognition and tracking
  • 4. Face recognition tracking
  • 5. Autonomous driving line patrol
  • 6. QR code motion control
  • 7. Gesture control of basic movement of the car
  • 8. Control the car movement with your palm
  • 9. Gesture control car action group
  • 10. Palm control of the two-dimensional gimbal servo
09. Lidar course
  • 1. Lidar avoid
  • 2. Lidar following
  • 3. Lidar guard
  • 4. Lidar patrol
  • 5. Gmapping mapping
  • 6. Cartographer mapping
  • 7. Navigation2 navigation avoid
  • 8. ROS Robot APP mapping
  • 9. ROS Robot APP navigation
10. Multi-machine course
  • 1. Multi-machine handle control
  • 2. Multi-machine keyboard control
  • 3. Multi-machine navigation
11. Linux basic course
  • 1. Introduction to Linux system
  • 2. Ubuntu file system
  • 3. Ubuntu common commands
  • 4. Ubuntu common editors
  • 5. Ubuntu software operation commands
  • 6. Virtual machine installation
  • 7. SSH remote control
  • 8. VNC remote control
  • 9. Transfer files remotely
  • 10. Driver library and communication
  • 11. Static IP and hotspot mode
  • 12. Bind device ID
  • 13. Capacity expansion and resource allocation
  • 14. Update system software sources
  • 15. Set root user password
  • 16. sudo free password
  • 17. Connect to WiFi network
  • 18. View system version
  • 19. Customized service management
  • 20. Back up system image
12. RPi basic setting course
  • 1. Update and upgrade operating system
  • 2. Introduction to raspi-config tool
  • 3. config.txt file description
  • 4. Network Configuration
  • 5. remote access
  • 6. Transfer files remotely
  • 7. Set display resolution and rotation
  • 8. Set screen to sleep
  • 9. Get real-time temperature of Raspberry Pi
  • 10. Play audio and video
  • 11. Using USB camera
  • 12. Using MIPI camera
13. Docker course
  • 1. Overview and installation
  • 2. Common commands
  • 3. Docker images deeply understand and publish images
  • 4. Docker hardware interaction and data processing
  • 5. Enter the robot's docker container
14. ROS2 basic course
  • 1. Introduction to ROS2
  • 2. ROS2 install Humble
  • 3. ROS2 development environment
  • 4. ROS2 workspace
  • 5. ROS2 function package
  • 6. ROS2 node
  • 7.ROS2 topic communication
  • 8.ROS2 service communication
  • 9.ROS2 action communication
  • 10.ROS2 custom interface message
  • 11.ROS2 parameter service case
  • 12.ROS2 meta-function package
  • 13.ROS2 distributed communication
  • 14.ROS2 DDS
  • 15.ROS2 time related API
  • 16.ROS2 common command tools
  • 17.ROS2 rviz2 use
  • 18.ROS2 rqt toolbox
  • 19.ROS2 Launch startup file configuration
  • 20.ROS2 recording and playback tool
  • 21.ROS2 URDF model
  • 22.ROS2 Gazebo simulation platform
  • 23.ROS2 TF2 coordinate transformation
15. microROS control board development environment
  • 1. Introduction to microROS control board
  • 2. Set up ESP32-IDF development environment
  • 3. ESP32-IDF configuration tool
  • 4. Install ESP32-microros components
  • 5. Install and start microROS agent
  • 6. Flash-tool burning firmware
16. ESP32 basic course
  • 1. Turn on the LED light
  • 2. Button function
  • 3. Drive the buzzer
  • 4. Serial communication
  • 5. Battery voltage detection
  • 6. Drive PWM servo
  • 7. Drive motor
  • 8. Read motor encoder data
  • 9. PID controls car speed
  • 10. Read IMU data
  • 11. Read radar data
  • 12. Flash access data
  • 13. Partition table and memory
  • 14. Bluetooth communication
  • 15. WiFi networking
  • 16. Robot kinematics analysis
  • 17.ROS-WiFi camera module
17. microROS basic course
  • 1. Publish topic
  • 2. Subscribe topic
  • 3. Multi-topic subscribe and publish
  • 4. Subscribe buzzer topics
  • 5. Subscribe PWM servo topics
  • 6. Subscribe speed control topics
  • 7. Release speed topic
  • 8. Release IMU data topic
  • 9. Publish lidar data topics
  • 10. Customized transmission method
Download
  • Mapping_APP(iOS_Android)
  • Source code
  • Hardware information
  • VM image file
  • RPi5 imgae file
  • Instruction Manual
  • 3D Model File
  • ROS2_Basic_VM
Download ZIP
FAQ
  • 1、1.USB camera abnormal termination

Welcome to MicroROS-Pi5 repository

当製品の日本語版マニュアル資料は、こちらからご取得ください。

9.ROS2 action communication

9.ROS2 action communication

 

1. Introduction to Action Communication

Action communication is a communication model with continuous feedback. Between the two communicating parties, the client sends request data to the server, and the server responds to the client. However, from the time the server receives the request to the time it generates the final response, it sends continuous feedback to the client.

The action communication client/server model is as follows:

image8

2. Example Introduction

The action client submits an integer data type N. The action server receives the request data and accumulates all integers between 1 and N, returning the final result to the action client. Each addition calculates the current computation progress and provides feedback to the action client.

3. Create a new function package

3.1. Create an action communication interface function package

  1. Action communication requires creating the action communication interface first.
  • Create a new pkg_interfaces function package in the src directory of the workspace.
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ros2 pkg create --build-type ament_cmake pkg_interfaces
  1. Next, create an action folder under the pkg_interfaces function package and create a new file called [Progress.action] within the action folder. The file contents are as follows:
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int64 num
---
int64 sum
---
float64 progress

image-20231030154108201

  1. Add some dependency packages to package.xml. The specific content is as follows:
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<buildtool_depend>rosidl_default_generators</buildtool_depend>
<exec_depend>rosidl_default_runtime</exec_depend>
<depend>action_msgs</depend>
<member_of_group>rosidl_interface_packages</member_of_group>
  1. Add the following configuration to CMakeLists.txt:
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find_package(rosidl_default_generators REQUIRED)
​
rosidl_generate_interfaces(${PROJECT_NAME}
  "action/Progress.action"
)

image-20231030154828498

  1. Compile the package:
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colcon build --packages-select pkg_interfaces

image-20250905142323197

  1. After compilation is complete, the C++ and Python files corresponding to the Progress.action file will be generated in the install directory of the workspace. You can also access the workspace in a terminal and verify the file definitions and compilation by running the following command:
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source install/setup.bash
ros2 interface show pkg_interfaces/action/Progress

Under normal circumstances, the terminal will output the same content as the Progress.action file.

image-20250820112138938

3.2. Creating the Action Communication Function Package

Create a new package called pkg_action in the src directory of the workspace.

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ros2 pkg create pkg_action --build-type ament_python --dependencies rclpy pkg_interfaces --node-name action_server_demo

After executing the above command, the pkg_action function package will be created, along with an action_server_demo node and the relevant configuration files.

image-20231030155311734

4. Server Implementation

4.1 Creating the Server

Next, edit [action_server_demo.py] to implement the server functionality and add the following code:

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import time
import rclpy
from rclpy.action import ActionServer
from rclpy.node import Node
​
from pkg_interfaces.action import Progress
​
​
class Action_Server(Node):
​
    def __init__(self):
        super().__init__('progress_action_server')
        # Creating an action server
        self._action_server = ActionServer(
            self,
            Progress,
            'get_sum',
            self.execute_callback)
        self.get_logger().info('动作服务已经启动!')
​
    def execute_callback(self, goal_handle):
        self.get_logger().info('开始执行任务....')
​
​
        # Generate continuous feedback;
        feedback_msg = Progress.Feedback()
​
        sum = 0
        for i in range(1, goal_handle.request.num + 1):
            sum += i
            feedback_msg.progress = i / goal_handle.request.num
            self.get_logger().info('连续反馈: %.2f' % feedback_msg.progress)
            goal_handle.publish_feedback(feedback_msg)
            time.sleep(1)
​
        # Generate the final response.
        goal_handle.succeed()
        result = Progress.Result()
        result.sum = sum
        self.get_logger().info('任务完成!')
​
        return result
​
​
def main(args=None):
​
    rclpy.init(args=args)
    # Call the spin function and pass in the node object
    Progress_action_server = Action_Server()
    rclpy.spin(Progress_action_server)
    Progress_action_server.destroy_node() 
    # Release resources
    rclpy.shutdown()

 

4.2 Edit the Configuration File

  • Open setup.py and add the following line to the console_scripts list:
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'action_server_demo = pkg_action.action_server_demo:main',

image-20231030164238858

4.3 Compile the Package

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colcon build --packages-select pkg_action

4.4 Run the Program

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ros2 run pkg_action action_server_demo

image-20231030164959631

In another terminal, enter:

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ros2 action list

image-20231030165029444

/get_sum is the action we need to call. To do so, enter the following command in the terminal:

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ros2 action send_goal /get_sum pkg_interfaces/action/Progress "{num: 10}"

Here we calculate the sum of the values ​​from 1 to 10:

image-20231030165504071

The upper part of the image above shows the server, and the lower part shows the client. You can see that the server continuously reports progress while calculating the sum from 1 to 10. Finally, the task is completed, and the client receives feedback that the sum is 55.

5. Client Implementation

5.1 Creating the Client

Create a new file, action_client_demo.py, in the same directory as action_server_demo.py.

image-20231030170243256

Next, edit action_client_demo.py to implement the server functionality and add the following code:

xxxxxxxxxx
import rclpy
from rclpy.action import ActionClient
from rclpy.node import Node
from pkg_interfaces.action import Progress
​
class Action_Client(Node):
    def __init__(self):
        super().__init__('progress_action_client')
        # Create an action client;
        self._action_client = ActionClient(self, Progress, 'get_sum')
​
    def send_goal(self, num):
        # Send a request;
        goal_msg = Progress.Goal()
        goal_msg.num = num
        self._action_client.wait_for_server()
        self._send_goal_future = self._action_client.send_goal_async(goal_msg, feedback_callback=self.feedback_callback)
        self._send_goal_future.add_done_callback(self.goal_response_callback)
​
    def goal_response_callback(self, future):
        # Process the feedback after the target sends it;
        goal_handle = future.result()
        if not goal_handle.accepted:
            self.get_logger().info('请求被拒绝')
            return
​
        self.get_logger().info('请求被接收,开始执行任务!')
​
        self._get_result_future = goal_handle.get_result_async()
        self._get_result_future.add_done_callback(self.get_result_callback)
​
    #Process the final response.
    def get_result_callback(self, future):
        result = future.result().result
        self.get_logger().info('最终计算结果:sum = %d' % result.sum)
        # 5. Release resources.
        rclpy.shutdown()
​
    # Processing continuous feedback;
    def feedback_callback(self, feedback_msg):
        feedback = (int)(feedback_msg.feedback.progress * 100)
        self.get_logger().info('当前进度: %d%%' % feedback)
​
​
def main(args=None):
    rclpy.init(args=args)
    action_client = Action_Client()
    action_client.send_goal(10)
    rclpy.spin(action_client)

 

5.2 Edit the Configuration File

  • Open setup.py and add the following line to the console_scripts list:
xxxxxxxxxx
'action_client_demo = pkg_action.action_client_demo:main'

image-20231030171045187

5.3 Compile the Package

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colcon build --packages-select pkg_action

image-20250905143944896

5.4 Run the Program

Execute the following command in a separate terminal:

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# Start the server node
ros2 run pkg_action action_server_demo
# Start the client node
ros2 run pkg_action action_client_demo

image-20231030171150033

The image above shows the server on the top and the client on the bottom. Here, we're calculating the sum of 1 to 10. You can see that the server continuously reports progress during the calculation. Finally, the task is completed, and the client receives feedback that the sum is 55.

ROS2 service communication
ROS2 custom interface message

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