yahboom
HomeLearn
Solution
Blog
Online Store
About Us
EN/中文
Raspbot V2📖
1.About Raspbot V2
  • 1. First trial
  • 2. Expansion board interface distribution
  • 3. About battery and charging
  • 4. Install servo PTZ
  • 5.Servo Gimbal Installation
  • 6. Important Notes (Read Before Starting)
2.Assembly
  • Installation Video
3.Car basic course
  • 0. Preparation before development
  • 1.Buzzer control
  • 2.Key reading
  • 3.RGB control
  • 4.Servo control (PTZ control)
  • 5.Motor control
  • 6.Printing ultrasonic data
  • 7.Tracking module status printing
  • 8.IR control key value printing
4.Car motion control course
  • 0.Mecanum wheel motion principle
  • 1.Car vertical movement
  • 2.Car diagonal movement
  • 3.Car sideways movement
  • 4.Car rotation movement
  • 5.Car patrol
5.Car advanced courses
  • 1.Infrared patrol car
  • 2.Ultrasonic avoid
  • 3.Ultrasonic follow
  • 4.Infrared tracking+ ultrasonic avoid
  • 5.Restricting
  • 6.Infrared remote control car
6.OpenCV courses
A. Getting Started with OpenCV
  • 1. Introduction to OpenCV
  • 2.OpenCV image reading and display
  • 3. OpenCV image writing
  • 4. OpenCV Image Quality
  • 5.OpenCV pixel operations
B. OpenCV geometric transformation
  • 1. Image scaling
  • 2. Image cutting
  • 3. Image translation
  • 4. Image mirroring
  • 5. Affine Transformation
  • 6. Image Rotation
  • 7. Perspective Transformation
C. OpenCV image processing and text line drawing
  • 1. Grayscale processing
  • 2. Image Binarization
  • 3. Edge Detection
  • 4. Line drawing
  • 5. Rectangle and circle drawing
  • 6. Text and image drawing
D. Image beautification
  • 1. Color Image Histogram
  • 2. Histogram Equalization
  • 3. Image repair
  • 4. Brightness enhancement
  • 5. Smooth and whiten
  • 6. Gaussian mean filtering
  • 7. Median Filter
E. Machine Learning
  • 1. KNN
  • 2. SVM
7.AI vision recognition course
  • 1.Camera driver tutorial
  • 2.Color recognition
  • 3.HSV value test
  • 4.Object Recognition
  • 5.QR code recognition
  • 6.Face recognition
  • 7.License Plate Recognition
  • 8. Human Pose Estimation
  • 9. Target detection
  • 10.yolov5-lite
  • 11. Gesture Recognition
  • 12. Face Detection
  • 13. Face effects
  • 14. 3D Object Recognition
  • 15. Paintbrush
  • 16. Finger control
8.AI vision interaction module
  • 1. Color tracking
  • 2. Color follows
  • 3. QR code recognition to control movement
  • 4. Face tracking
  • 5. Face following
  • 6. Visual tracking
  • 7. Garbage identification
  • 8. Track map Autopilot(purchased separately)
  • 9. Gesture following
9.Voice control basic course(For Superior Kit)new
  • 1.Voice control car movement
  • 2.Voice control RGB light
  • 3.Voice control color recognition
  • 4.Voice control autonomous driving
  • 5.Voice control car tracking
10.AI large model knowledge(For Superior Kit)new
  • 1.AI large model types and principles
  • 2.RAG retrieval enhancement and model training samples
  • 3.Embodied intelligent robot system architecture
  • 4.Embodied intelligent functions core source code
  • 5.Configure AI large model(Required)
11.AI Large Model Development(For Superior Kit & Reference)new
  • 1.Register a model service provider account
  • 2. Configuring API-KEY(Optional)
  • 3. Introduction to Dify
  • 4. Basic Dify Features
  • 5. Deploy the RAG knowledge base
  • 6. AI Large Model Development - chatbot
  • 7. RAG knowledge base + chatbot
  • 8. AI agent workflow
  • 9. Custom wake-up response
  • 10. Core module testing tools
12.AI large basic course(For Superior Kit)new
  • 1.Free conversation
  • 2.Text-to-picture
  • 3.Scene description
  • 4.Video description
  • 5.Intelligent action choreography
  • 6.Dual-model agent application
13.ROS2-Robot chassis control course
  • 1. Robot information release
  • 2. Robot keyboard control
  • 3. URDF Model
14.ROS2-OpenCV course
  • 1.ROS+Opencv application
  • 2. AR Vision
  • 3. Mediapipe fun gameplay
  • 4. Gesture control car movement
  • 5. Gesture control car actions
  • 6. Palm control car movement
  • 7. Palm control servo PTZ
  • 8. Visual tracking
  • 9. AprilTag code recognition
  • 10. AprilTag tag code tracking
  • 11. AprilTag tag code follow
15.Development environment course
  • 1. Introduction to Raspberry Pi 5
  • 2. Image writing and backup
  • 3. Start the Raspberry Pi 5
  • 4. Remote Access
  • 5. Remote file transfer
  • 6. Common Linux commands and use of vim editor
  • 7. Install Raspbot V2 driver library
  • 8. Jupyter Lab environment construction
  • 9. Jupyter Lab plugin installation
  • 10. Basic use of Jupyter Widgets
16.Raspberry Pi basic settings
  • 1.Update and upgrade the operating system
  • 2. Introduction to raspi-config tool
  • 3. config.txt file description
  • 4. Network Configuration
  • 5. Set display resolution and rotation
  • 6. Set screen sleep
  • 7. Get real-time temperature of RPi
  • 8. Play audio and video
  • 9. Use USB Camera
  • 10.Use MIPI camera
17.Docker course
  • 1. Overview and installation
  • 2. Common commands
  • 3. Understand and publish images
  • 4. Docker data processing
  • 5. Enter docker container
18.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
Download
  • APP(iOS/Android)
  • Code
  • System_File
  • Instruction Manual
  • Hardware_Info
  • 3D_Model_File
  • ROS2_Basic_VM
Download ZIP

Welcome to Raspbot V2 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。

1. Robot information release

Robot information release

1. Program function description

After the car starts the chassis drive, it will publish the data of sensor modules such as ultrasonic and four-way patrol. You can run commands in docker to query this information, and you can also publish the control data of sensors such as speed, buzzer, RGB light bar, etc.

2. Query car information

2.1. Enter the car docker

Open a terminal and enter the following command to enter docker,

./docker_ros2.sh

The following interface appears, indicating that you have successfully entered docker. Now you can control the car through commands.

image-20240814152903441

xxxxxxxxxx
ros2 launch yahboomcar_bringup bringup.launch.py

Start the chassis drive, as shown in the figure below,

image-20240814182020132

Open a new terminal and enter the same docker. Change the following da8c4f47020a to the ID displayed in the actual terminal.

xxxxxxxxxx
docker ps
xxxxxxxxxx
docker exec -it da8c4f47020a   /bin/bash

Enter the following command to query the node,

xxxxxxxxxx
ros2 node list

image-20240814152108224

Then enter the following command to query which topics the node has published/subscribed to,

xxxxxxxxxx
ros2 node info /driver_node 

image-20240814152722539

It can be seen that the subscribed topics are,

/buzzer: buzzer control

/cmd_vel: car speed control

/rgblight: RGB light bar control

/servo: s1 servo pan/tilt control, s2 servo pan/tilt control

The published topics are,

/ultrasonic: ultrasonic module data

/line_sensor: four-way line patrol module data

We can also query the topic command, terminal input,

xxxxxxxxxx
ros2 topic list

image-20240814153016327

2.3. Query topic data

Query ultrasonic data,

xxxxxxxxxx
ros2 topic echo /ultrasonic

image-20240814153213392

Query the data of the four-way line patrol module.

xxxxxxxxxx
ros2 topic echo /line_sensor

image-20240814153345094

3. Publish car control information

3.1. Control the buzzer

First query the following buzzer topic related information, terminal input,

xxxxxxxxxx
ros2 topic info /buzzer

image-20240814153448391

The data type is std_msgs/msg/Bool. Then enter the following command to turn on the buzzer, and enter in the terminal,

xxxxxxxxxx
ros2 topic pub /buzzer std_msgs/msg/Bool "data: 1"

image-20240814153708279

Enter the following command to turn off the buzzer, terminal input,

xxxxxxxxxx
ros2 topic pub /buzzer std_msgs/msg/Bool "data: 0"

image-20240814153733420

3.2. Release speed control information

We assume that the speed of the car is 0.1 of the linear speed, and the terminal input is,

xxxxxxxxxx
#Valid value range
#linear:    x[-1,1] y[-1,1] z
#angular:   x       y       z[-3,3]
xxxxxxxxxx
ros2 topic pub -1 /cmd_vel geometry_msgs/msg/Twist "{linear: {x: 0.1, y: 0.0, z: 0.0}, angular: {x: 0.0, y: 0.0, z: 0.0}}"

image-20240814154941646

If parking, input

xxxxxxxxxx
ros2 topic pub -1 /cmd_vel geometry_msgs/msg/Twist "{linear: {x: 0.0, y: 0.0, z: 0.0}, angular: {x: 0.0, y: 0.0, z: 0.0}}"

3.3. Control RGB light bar

We assume that the published RGB value is 255,0,0, and the terminal input is

xxxxxxxxxx
ros2 topic pub -1 /rgblight std_msgs/msg/Int32MultiArray "data: [255, 0, 0]" 

image-20240814160415920

Turn off the light and enter

xxxxxxxxxx
ros2 topic pub -1 /rgblight std_msgs/msg/Int32MultiArray "data: [0, 0, 0]" 

3.4. Control the PTZ Servo

It should be noted that the range of the s1 servo is [0,180], and the range of the s2 servo is [0,110]. If the value exceeds the range, the servo will not rotate.

We assume that the s1 servo is controlled to rotate to 90 degrees and the s2 servo is controlled to rotate to 25 degrees. Then the terminal input is,

xxxxxxxxxx
ros2 topic pub -1 /servo yahboomcar_msgs/msg/ServoControl "{'servo_s1': 90, 'servo_s2': 25}"

3.5. Complete chassis driver

3.5.1. Startup program
xxxxxxxxxx
ros2 launch yahboomcar_bringup yahboomcar_bringup.launch.py

Start the chassis drive, as shown below.

20240814184257

Enter the following command in the terminal to query the node:

xxxxxxxxxx
ros2 node list

image-20240814190607693

Enter the following command to view the communication diagram between nodes.

xxxxxxxxxx
ros2 run rqt_graph rqt_graph

image-20240814190856559

Enter the command to view the relevant information of the node

xxxxxxxxxx
ros2 node info /driver_node

image-20240814191116682

3.5.2. Parsing launch files
​x
from ament_index_python.packages import get_package_share_path

from launch import LaunchDescription
from launch.actions import DeclareLaunchArgument
from launch.conditions import IfCondition, UnlessCondition
from launch.substitutions import Command, LaunchConfiguration

from launch_ros.actions import Node
from launch_ros.parameter_descriptions import ParameterValue

import os
from ament_index_python.packages import get_package_share_directory

from launch.actions import IncludeLaunchDescription
from launch.launch_description_sources import PythonLaunchDescriptionSource

def generate_launch_description():
    # 配置参数

    description_launch = IncludeLaunchDescription(
        PythonLaunchDescriptionSource([os.path.join(
        get_package_share_directory('yahboomcar_description'), 'launch'),
         '/description_launch.py'])
    )  

    driver_node = Node(
        package='yahboomcar_bringup',
        executable='Mcnamu_driver',
    )

    # 返回LaunchDescription对象
    return LaunchDescription([
        driver_node,
        description_launch
    ])

  • The launch file starts the following nodes:

    • driver_node: chassis driver data node;
    • description_launch: load URDF model.

 

Dual-model agent application
Robot keyboard control

COMPANY

  • About us
  • Team Style
  • Blog

LEARNING & EXPLORATION

  • Tutorials
  • Edge AI hardware
  • Educational robots
  • Embedded intelligent hardware

WHERE TO BUY

  • Yahboom Online Store
  • Amazon
  • Alibaba
  • AliExpress
  • Mercado

TECHNOLOGY SUPPORT

  • Email: support@yahboom.com

BE A DISTRIBUTOR

  • Email: sales@yahboom.com
QR Code

Copyright © 2017-2026 Yahboom. All Rights Reserved.

EN/中文