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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

1. Introduction and use of lidar

1. Introduction and use of lidar

1. Introduction and use of lidar1.1, Program Function Description1.2, Program code reference path1.3, Program startup1.4, Introduction to MS200 lidar1.4.1, Overview1.4.2, Distance measurement principle1.4.3 Baud rate1.4.4 Specifications

Before driving the laser lidar, you need to identify the olidar lidar device on the car side. The environment has been set up in the system image. After connecting to the car through SSH or VNC, enter in the terminal:

x
ll /dev/oradar

image-20241113143651020

The result shows lidar and its corresponding port, indicating that the lidar device is connected successfully. If no result is displayed, you can try to re-plug the lidar USB.

1.1, Program Function Description

After the program runs, start the olidar MS200 laser lidar, turn on the lidar scanning data, and visualize the laser lidar scanning data in rviz on the virtual machine side.

1.2, Program code reference path

After SSH connects to the car, the function source code for starting the lidar is located at,

x
/home/sunrise/software/library_ws/src/oradar_lidar/launch/ms200_scan.launch

1.3, Program startup

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

x
ros2 launch oradar_lidar ms200_scan.launch.py

Open the virtual machine terminal and run,

x
ros2 launch yahboomcar_rviz yahboomcar_laser_launch.py 

image-20241113145029211

You can use the following command to print the data scanned by the lidar,

xxxxxxxxxx
ros2 topic echo /scan

image-20241113145343649

1.4, Introduction to MS200 lidar

1.4.1, Overview

Single-line laser lidar refers to a lidar whose laser source emits a single-line beam. It is divided into triangulation and TOF laser lidar, and is mainly used in the field of robots. It has fast scanning speed, high resolution and high reliability. Compared with multi-line laser lidar, single-line laser lidar has faster response in angular frequency and sensitivity, so it is more accurate in the distance and accuracy of obstacle measurement.

1.4.2, Distance measurement principle

The measurement principle of Oruida MS200 is TOF ranging method.

TOF laser lidar is based on measuring the flight time of light to obtain the distance of the target object. Its working principle is mainly manifested as a beam of modulated laser signal emitted by a laser transmitter, which is received by a laser detector after being reflected by the object to be measured. The distance of the target can be calculated by measuring the phase difference between the emitted laser and the received laser.

1.4.3 Baud rate

The baud rate used by the MS200 lidar is 230400.

1.4.4 Specifications

1684742147290

Among them, the parameters such as ranging range, measurement accuracy, rotation speed, and angular resolution are all important indicators of lidar working performance.

URDF Model
Lidar obstacle avoidance

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