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RDK X3 Robot📖
01. About RDK-X3-Robot
1. Instructions
  • 1. Introduction
  • 2. FAQ
  • 3. Battery and charger use precautions
  • 4.TF card expand capacity
2. Common problem analysis
02. Assembly video
  • Part1-Install Motor
  • Part2-Install Battert Fixing Column
  • Part3-Install Motor Coupling
  • Part4-Install Mecanum wheel
  • Part5-Install Expansion Board
  • Part6-Wiring Show
  • Part7-Install Main Control Board
  • Part8-Install Car Top Plate and Antenna
  • Part9-Install OLED Screen
  • Part10-Install Depth Camera(Optional)
  • Part11-Install OLED Screen
  • Part12-Install HD Camera
  • Part13-Install Top Plate
  • Part14-Install Right Side Plate
  • Part15-Motor Wiring Show
  • Part16-lnstall Car Body
  • Part17-Install Battery
  • Part18-Install Lidar
03. Remote control tutorial
  • 1. The phone APP remote tutorial
  • 2. USB wireless controller remote tutorial
04. ROS functional tutorial
  • 1. Introduction of extension board
  • 2. Set up STM32 development environment
  • 3. Key control buzzer sound
  • 4. FreeRTOS application
  • 5. Serial communication
  • 6. SBUS model remote control
  • 7. CAN bus communication
  • 8. RGB color light strip
  • 9. Timer interrupt control PWM servo
  • 10. Control serial steering gear
  • 11. Nine-axis attitude sensor to obtain data
  • 12. Control motor forward and reverse
  • 13. The timer captures encoder data
  • 14. Theory of robot kinematics analysis
  • 15. PID control robot motion
05. Basic control tutorial
  • 1. Update the firmware of the expansion module
  • 2. Install the Python driver library
  • 3. Set the type of bottom car
  • 4. Open and close the APP program control
  • 5. Turn hotspot mode on and off
  • 6. The buzzer blows
  • 7. Control the motor forward and reverse
  • 8. Control robot movement
  • 9. OLED display
  • 10. Control fan and lamp effect
06. Development environment setup
  • 1. Virtual Machine
  • 2. Linux Basics
  • 3. Remote connection
  • 4. Multi-computer communication configuration
  • 5. Bind the device ID
  • 6. Image installation and backup
07. 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
08. Robot chassis control
  • 1. PID algorithm theory
  • 2. Robot information release
  • 3. Robot control
  • 4. Robot state estimation
  • 5. Robot calibration
  • 6. Robot trajectory tracking
  • 7. URDF model
09. Lidar courses
  • 1. Introduction and use of lidar
  • 2. Lidar obstacle avoidance
  • 3. Lidar following
  • 4. Lidar guard
  • 5. Patrol
  • 6. gmapping algorithm
  • 7. cartographer algorithm
  • 8. Navigation and obstacle avoidance
  • 9. App mapping and navigation
10. OpenCV courses
  • 1. Introduction to OpenCV
  • 2. OpenCV geometric transformation
  • 3. OpenCV image processing
  • 4. OpenCV image beautification
  • 5. Qr code creation and identification
11. MIPI camera course
  • 1. Camera driver
  • 2. Adjust the color HSV value
  • 3. Color recognition
  • 4. Color tracking
  • 5. Color follow
  • 6. Qr code command
  • 7. Face detection
  • 8. Object detection
  • 9. Visual Inspection -OpenCV
  • 10. Visual inspection - Deep learning
  • 11. Human tracking
  • 12. Gesture control
12. Depth Camera courses
  • 1. Use depth camera
  • 2. Calibration of camera internal reference
  • 3. ROS+OpenCV Foundation
  • 4. AR vision
  • 5. Color tracking
  • 6. Object tracking
13. Multi vehicle control
  • 1. Multi-vehicle synchronous control
  • 2. Multi-vehicle navigation
Remote login control
  • 1. VNC and SSH remote login
  • 2. Jupyter lab login and case code running
Download
  • RemoteCtrl_APP(iOS/Android))
  • Mapping_APP(iOS_Android)
  • Code
  • System File
  • VM_File
  • Manual
  • Software_File
  • Hardware_File
  • ROS2_Basic_VM
Download ZIP

Welcome to RDK X3 Robot repository

4. Robot state estimation

4. Robot state estimation

4. Robot state estimation4.1 Program function Description4.2. Program Code Reference path4.3. Program Startup4.3.1. Launch command4.3.2. View the node communication graph4.4 launch file parsing

 

4.1 Program function Description

After the program is run, combined with the imu data read from the ROS expansion board and the speed vel data, output an odom data that integrates imu and odom data, which can be applied to the positioning function.

4.2. Program Code Reference path

After SSH connection car, the location of the function source code is located at,

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/userdata/yahboomcar_ws/src/yahboomcar_bringup/launch/yahboomcar_bringup_launch.py

ekf fusion program code reference path,

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/userdata/yahboomcar_ws/src/robot_localization/launch/ekf.launch.py

4.3. Program Startup

4.3.1. Launch command

After SSH connects to the car, terminal input,

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ros2 launch yahboomcar_bringup yahboomcar_bringup_launch.py

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4.3.2. View the node communication graph

Open the VM terminal and enter.

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ros2 run rqt_graph rqt_graph

[Note] As RDK-X3 board does not provide a graphical desktop environment, ros rqt related operations need to be implemented on the PC side (virtual machine side). That is, as long as the communication between the PC and the car is normal, you can directly run the relevant instructions without SSH connection to the car after opening the terminal.

1684478687053

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It can be seen from the node input and output in the red box in the above figure that /ekf_filter_node receives odom_raw data and imu_data data for fusion, and finally outputs and publishes an odom data, which can be viewed through ros2 node tool.

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ros2 node info /ekf_filter_node

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4.4 launch file parsing

Let's look at the main relevant nodes of the launch file.

  • /driver_node: start the car chassis, obtain the wheel speed vel data and publish it to the /base_node node, obtain the imu data and publish it to the /imu_filter_node node.
  • /base_node: receives vel data, converts it into odom_raw data through calculation, and publishes it to the /ekf_node node.
  • /imu_filter_node: receives the imu data released by the chassis, filters it by its own algorithm, and sends the filtered imu/data data to the /ekf_node.
  • /ekf_node: receives odom data published by /base_node and imu/data published by /imu_filter_node, uses its own algorithm to fuse and publish odom data.
Robot control
Robot calibration

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