yahboom
HomeLearn
Solution
Blog
Online Store
About Us
EN/中文
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。

1. Monocular camera calibration

Camera calibration

Wiki:http://wiki.ros.org/camera_calibration

Ordinary camera:https://github.com/bosch-ros-pkg/usb_cam.git

Monocular teaching:http://wiki.ros.org/camera_calibration/Tutorials/MonocularCalibration

Due to some internal and external reasons of the camera, the image will be greatly distorted, mainly radial deformation and tangential deformation, causing the straight line to become curved. The farther the pixel is from the center of the image, the more serious the distortion will be. In order to avoid errors caused by data sources, the parameters of the camera need to be calibrated. Calibration essentially uses a known and determined spatial relationship (calibration plate) to reversely deduce the inherent and real parameters of the camera (internal parameters) by analyzing the pixels of the photographed pictures.

1、Preparation before calibration

  • A large chessboard of known dimensions. This tutorial uses a 9x6 checkerboard and a 20mm square, which needs to be flattened during calibration. The calibration uses the internal vertices of the checkerboard, so a "10x7" checkerboard uses the internal vertex parameters "9x6", as shown in the example below. Calibration boards of any specifications are acceptable, just change the parameters. An open area without obstacles or calibration board patterns

  • Monocular camera publishing images via ROS

2、Start calibration

Install the calibrated function package camera_calibration and enter it in the docker terminal (the factory docker is already installed and does not need to be reinstalled)

sudo apt install ros-humble-camera-calibration*

Start the camera before calibration, and then turn off the camera until all calibrations are completed. Start the camera and enter it in the Docker terminal.

xxxxxxxxxx
ros2 run usb_cam  usb_cam_node_exe

Use the following command to view the topic, enter in the Docker terminal.

image-20240123181535694

The topic we need to use to calibrate RGB color images is /image_raw.

Run the calibrated program and enter in the Docker terminal.

xxxxxxxxxx
ros2 run camera_calibration cameracalibrator --size 9x6 --square 0.02 --ros-args --remap /image:=/image_raw

size:Calibrate the number of internal corner points of the checkerboard, for example, 9X6, with a total of six rows and nine columns of corner points.

square:The side length of the checkerboard, in meters.

Topic name: /image_raw

1706005168211_35AB1EAE-8F46-435c-AFFE-1AC1CE945026

X:The checkerboard moves left and right in the camera field of view

Y:The checkerboard moves up and down in the camera's field of view

Size :The checkerboard moves forward and backward in the camera's field of view

Skew:The tilt and rotation of the checkerboard in the camera's field of view

As shown in the picture above, you need to collect the image by flipping it up and down, front and back, left and right, so that the X, Y, Size and Skew on the right turn green, as shown in the picture below, then click CALIBRATE to start calibration.

1706005190581_CA35EDDB-6837-4171-806A-9BFFE29F9149

After the calibration is completed, click SAVE, as shown in the figure below.

image-20240123182058311

The calibration results are saved to [/tmp/calibrationdata.tar.gz], and the saving path is the terminal directory where the calibration program is started. After the calibration is completed, you can move out the [/tmp/calibrationdata.tar.gz] file to see the content.

xxxxxxxxxx
sudo mv /tmp/calibrationdata.tar.gz ~

docker terminal input.

xxxxxxxxxx
cd ~
tar -xvf calibrationdata.tar.gz

You will get the calibrated png file, ost.yaml and ost.txt files in the terminal directory.

When starting the USB camera, you need to load parameters. Therefore, after calibration, you need to replace the parameters with the original built-in parameters. Rename the calibrated ost.yaml to camera_info.yaml, then replace the original camera_info.yaml, and enter it in the docker terminal.

x
#First copy the file to /opt/ros/foxy/share/usb_cam/config
sudo cp ost.yaml /opt/ros/foxy/share/usb_cam/config
#Switch to the /opt/ros/foxy/share/usb_cam/config directory
cd /opt/ros/foxy/share/usb_cam/config
#Back up the original camera_info.yaml
sudo mv camera_info.yaml camera_info_BK.yaml
#Rename ost.yaml to camera_info.yaml
sudo mv ost.yaml camera_info.yaml

 

 

 

 

 

 

 

 

 

 

 

 

10 .Gesture recognition
Color tracking

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
QR Code

Copyright © 2017-2026 Yahboom. All Rights Reserved.

EN/中文