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RDK X5 Robot📖
01. RDK-X5-Robot Introduction
  • 1.Introduction
  • 2.Common Problem Analysis
  • 3.Battery and charger usage precautions
  • 4.TF card expand capacity
02. Assembly Tutorial
  • Assembly Tutorial
  • Assembly Video-1
  • Assembly Video-2
  • Assembly Video-3
  • Assembly Video-4
03. Remote Control Course
  • 1.Mobile APP remote control
  • 2.USB Wireless Controller Remote Control
04. ROS Driver Board Course
  • 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 Course
  • 1.Update expansion board firmware
  • 2.Install Python driver library
  • 3.Set the car type
  • 4.Open and close APP program control
  • 5.Turn hotspot mode on and off
  • 6.Buzzer sound
  • 7.Control the motor to rotate forward and reverse
  • 8.Controlling robot movement
  • 9.OLED display
  • 10.Control fans and lighting effects
06. Development Environment
  • 1. Virtual machine installation and use
  • 2. Linux Basics
  • 3. Remote connection
  • 4. Multi-machine communication configuration
  • 5. Bind 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 Course
  • 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 Course
  • 1. Introduction and use of lidar
  • 2. Lidar obstacle avoidance
  • 3. Lidar tracking
  • 4. Lidar guard
  • 5. Lidar patrol
  • 6. gmapping mapping algorithm
  • 7. Cartographer mapping algorithm
  • 8. Navigation and obstacle avoidance
  • 9. App Mapping and Navigation
10. OpenCV Course
  • 1. Getting started with OpenCV
  • 2. OpenCV geometric transformation
  • 3. OpenCV Image Processing
  • 4. OpenCV image beautification
  • 5. QR code creation and recognition
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 instructions
  • 7. Face Detection
  • 8. Object Detection
  • 9. Visual line patrol-OpenCV
  • 10. Visual line patrol-deep learning
  • 11. Human body tracking
  • 12. Gesture control
12. Depth Camera Course
  • 1. Use of Depth Camera
  • 2. Camera intrinsic calibration
  • 3. ROS+OpenCV Basics
  • 4. AR Vision
  • 5. Color Tracking
  • 6. Object Tracking
  • 7. RTAB-Map 3D Mapping Navigation
13. Multi-robot Synchronous Control
  • Multi-vehicle synchronous control
Remote login control
  • 1. VNC and SSH remote login
  • 2. Jupyter lab login and case code running
Download
  • System_File
  • Code
  • VM_File
  • Software_Tools
  • Hardware_Info
  • Firmware
  • Instruction_Manual
  • ROS2_Basic_VM
Download ZIP

Welcome to RDK X5 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, Start command4.3.2, View the node communication diagram4.4, launch file analysis

4.1. Program function description

After the program runs, it combines the imu data and speed vel data read from the ROS expansion board to output an odom data that integrates imu and odom data. This data can be used when performing positioning functions.

4.2, Program code reference path

After SSH connects to the car, the location of the function source code is,

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/home/sunrise/yahboomcar_ws/src/yahboomcar_bringup/launch/yahboomcar_bringup_launch.py

ekf fusion program code reference path,

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/home/sunrise/yahboomcar_ws/src/robot_localization/launch/ekf.launch.py

4.3, Program startup

4.3.1, Start command

After SSH connects to the car, enter in the terminal,

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ros2 launch yahboomcar_bringup yahboomcar_bringup_launch.py

4.3.2, View the node communication diagram

Open the virtual machine terminal and enter,

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ros2 run rqt_graph rqt_graph

[Note] Since Xuripi does not provide a graphical desktop environment, all ROS rqt-related operations must be implemented on the PC side (virtual machine side). That is, as long as the communication between the PC side and the car side is normal, you can open the terminal without SSH connection to the car and directly run the relevant instructions.

image-20241125195936304

Mainly look at the node input and output in the red box in the above figure. It can be seen that /ekf_filter_node receives odom_raw data and imu_data data for fusion, and finally outputs and publishes an odom data. We can view it through the ros2 node tool, terminal input,

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ros2 node info /ekf_filter_node

image-20241125200002718

4.4, launch file analysis

Let's take a look at the main related nodes of the launch file,

  • /driver_node: Start the car chassis, obtain the wheel speed vel data, publish it to the /base_node node, obtain imu data, and publish it to the /imu_filter_node node;

  • /base_node: Receive vel data, convert it into odom_raw data through calculation, and publish it to the /ekf_node node;

  • /imu_filter_node: Receive the imu data published by the chassis, filter it through its own algorithm, and publish the filtered imu/data data to the /ekf_node node;

  • /ekf_node: Receive the odom data published by the /base_node node and the imu/data data published by the /imu_filter_node, merge them through its own algorithm, and publish the odom data.

Robot control
Robot calibration

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