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ROSMASTER R2📖
1.Preparation and First Trial
  • 1.1 Accessories introduction
  • 1.2 Precautions for battery
  • 1.3 First Trial
2.Assembly steps
  • Installaction Video
3.ROS1-Remote control course
  • 3.1 APP remote control
  • 3.2 Model aircraft remote control
  • 3.3 Handle remote control
4.ROS1-Hardware course
  • 4.1 About expansion board_V3.0
  • 4.1 About expansion board_V1.0
  • 4.2 STM32 Development environment
  • 4.3 Button to control the buzzer to whistle
  • 4.4 FreeRTOS application
  • 4.5 Serial communication
  • 4.6 SBUS model aircraft remote control
  • 4.7 CAN bus communication
  • 4.8 RGB colorful light bar
  • 4.9 Timer interrupt to control PWM servo
  • 4.10 Control serial port servos
  • 4.11 Nine-axis attitude sensor to obtain data
  • 4.12 Control motor
  • 4.13 Timer captures the encoder data
  • 4.14.1 Kinematic Analysis of Mecanum Wheel
  • 4.14.2 Kinematics Analysis of Ackermann Car
  • 4.15 PID control robot movement
5.ROS1-Basic course
  • 5.1 Update the firmware
  • 5.2 Turn off the self-starting process at startup
  • 5.3 Install the Rosmaster driver library
  • 5.4 Buzzer whistle
  • 5.5 Control PWM servo
  • 5.6 RGB colorful light bar special effects display
  • 5.7 Control motor
  • 5.8 Control robot movement
  • 5.9 Control Serial Servo
6.ROS1-Linux operating system
  • 6.1 Virtual machine installation and use
  • 6.2 Linux basics
  • 6.3 Remote control
  • 6.4 Multi-machine communication configuration
  • 6.5 Static IP and hotspot mode
  • 6.6 Bind the device ID
  • 6.7 Web page real-time monitoring
  • 6.8 Expansion tutorial
  • 6.9.1 Jetson Nano write sytem
  • 6.9.2 Jetson Xavier NX write system
  • 6.9.3 Jetson TX2 NX write system
  • 6.9.4 Raspberry Pi write system
7.ROS1-Docker-pi5
  • 1、Docker overview and docker installation
  • 2、Common commands for docker image containers
  • 3、Docker images deeply understand and publish images
  • 4、Docker hardware interaction and data processing
  • 5、Enter the bot's docker container
  • 6、Robot development environment construction in Docker
  • 7、How customers can update docker images in the future
8.ROS1-ROS basic course
  • 1.ROS introduction
  • 2.ROS installation
  • 3.ROS common command tools
  • 4.ROS workspace
  • 5.ROS function package
  • 6.ROS node
  • 7.ROS topic publisher
  • 8.ROS topic subscribers
  • 9.ROS service client
  • 10.ROS service server
  • 11.ROS action client
  • 12.ROS action server
  • 13.ROS custom message reception
  • 14.ROS-launch file
  • 15.ROS-TF transformation
  • 16.ROS parameter service
  • 17.ROS-rviz use
  • 18.ROS-rqt tool usage
  • 19.Topic message recording and playback
  • 20.urdf model introduction
  • 21.gazebo introduction
  • 22.ROS distributed communication
9.ROS1-OpenCV courses
  • 9.1 Getting started with Open Source CV
  • 9.2 Geometric transformation
  • 9.3 Image processing and drawing text line segments
  • 9.4 Image beautification
  • 9.5 Opencv application
  • 9.6 AR vision
  • 9.7 AR QR code
  • 9.8 ROS+Opencv foundation
  • 9.9 ROS+Opencv application
  • 9.10 Data transformation and point cloud
  • 9.11 MediaPipe development
10.ROS1-Robot control course
  • 10.1 PID algorithm theory
  • 10.2 Robot PID debugging
  • 10.3 Robot information release
  • 10.4 Robot keyboard control
  • 10.5 Robot handle control
  • 10.6 Robot state estimation
  • 10.7 Robot calibration
  • 10.8 Robot URDF model
11.ROS1-Depth camera course
  • 11.1 How to use the Astra camera
  • 11.2 Astra camera calibration
  • 11.3 Astra Color Tracking
  • 11.4 Astra Object Tracking
  • 11.5 Visual tracking autopilot
  • 11.6 Pure visual 2D mapping and navigation
  • 11.7 RTAB-Map 3D mapping navigation
  • 11.8 ORB_SLAM2 basics
  • 11.9 ORB_SLAM2_Octomap
12.ROS1-Lidar course
  • 11.1 Lidar basic-SLAM
  • 11.1 Lidar basic-EAI
  • 11.2 Lidar avoiding
  • 11.3 Lidar guard
  • 11.4 Lidar follow
  • 11.5 Patrol game
  • 11.6 gmapping mapping
  • 11.7 hector mapping
  • 11.8 karto mapping
  • 11.9 cartographer mapping
  • 11.10 rrt_exploration mappin
  • 11.11 AMCL
  • 11.12 Navigation and avoiding
  • 11.13 APP mapping and navigation
  • 11.14 TEB path planning algorithm
13.ROS1-Multi-robot control course
  • 13.1 Multi-machine handle control
  • 13.2 Multi-machine navigation
  • 13.3 Multi-machine formation
  • 13.4 Multi-machine surround
14.ROS1-Deep learning courses
  • 14.1 KNN recognizes handwritten digits
  • 14.2 Basic use of TensorFlow
  • 14.3 Basic use of PyTorch(jetson)
  • 14.4 yolov5 model training(jetson)
  • 14.5 yolov5+tensorrt acceleration(jetson)
  • 14.6 yolov4-tiny
15.ROS1-Voice control courses
  • 15.0 How to use old voice module in new image
  • 15.1 Introduction of voice control module-NEW
  • 15.2 Voice control module port binding-NEW
  • 15.1 Introduction of voice control module-Old
  • 15.2 Voice control module port binding-Old
  • 15.3 Voice control car movement
  • 15.4 Voice control Autopilot
  • 14.5 Voice control color recognition
  • 15.6 Voice control color tracking
  • 15.7 Voice control multi-point navigation
16.ROS1-Model training Autopilot
  • 16.0 ReadMe
  • 16.1 yolov5 to train traffic signs
  • 16.2 TensorRt acceleration identification mark
  • 16.3 Road sign indication function description
  • 16.4 Collect data
  • 16.5 Training model
  • 16.6 Model transformation and application
  • 16.7 AI Autopilot
17. ROS2-Remote control course
  • 1. APP remote control
  • 2. Model aircraft remote control
  • 3. Handle remote control
18.ROS2-Hardware course
  • 1. Expansion board introduction_V3.0
  • 1. Expansion board introduction_V1.0
  • 2. STM32 development environment build
  • 3. Key control buzzer sounding
  • 4. FreeRTOS applications
  • 5. Serial communication
  • 6. SBUS model airplane remote control
  • 7. CAN bus communication
  • 8. RGB colorful light bar
  • 9. Timer interrupt control PWM servos
  • 10. Control serial servos
  • 11. Nine-axis attitude sensor acquires data
  • 12. Control motor forward and reverse
  • 13. Timer Capture Encoder Data
  • 14. Theory of Robot Kinematics Analysis
  • 14.1.Mecanum wheel
  • 14.2.Ackerman
  • 14.3.4WD
  • 15. PID control of robot motion
19. ROS2-Basic course
  • 1. Update the firmware of the expansion board
  • 2.Close the large self-starting program at boot
  • 3. Install Rosmaster driver library
  • 4. Buzzer sounding
  • 5. Control PWM servo
  • 6. RGB colorful light bar special effects show
  • 7. Control motor forward and reverse
  • 8. Controlling robot motion
  • 9. Control serial servos
20. ROS2-Linux operating systemnew
  • 01. Virtual Machines
  • 02. Linux Basics
  • 03. Remote control
  • 04. Multi-computer communication configuration
  • 05. Static ip and hotspot mode
  • 06. Bind device ID
  • 07.Webpage real-time monitoring
  • 08. Expansion Tutorial
  • 09-1.Jetson Nano write system file
  • 09-2. Raspberry Pi write system file
  • 09-3.Orin write system
  • 10.Jetpack old system upgraded to SUPER systemnew
21.ROS2 -Docker(Nano Pi)
  • 1. docker overview and docker installation
  • 2. docker image container common command
  • 3. docker image in-depth understanding and publishing images
  • 4. docker hardware interaction and data processing
  • 5. Enter the docker container of the robot
  • 6. docker in the robot development environment build
  • 7. Customer's method of updating docker images in the future
22.ROS2- ROS2 Basic Tutorial
  • 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
23. ROS2-Robot control course
  • 1. PID algorithm theory
  • 2. Robot information release
  • 3. Robot control
  • 4. Robot state estimation
  • 5. Robot calibration
  • 6. URDF model
24. ROS2-Lidar course
  • 1-1. Introduction and use of SLAM lidar
  • 1-2. Introduction and use of 4ROS lidar
  • 2. Lidar obstacle avoidance fun gameplay
  • 3. Lidar tracking fun gameplay
  • 4. Patrol function play
  • 5. gmapping map building algorithm
  • 6. cartographer building algorithm
  • 7. Navigation and obstacle avoidance
  • 8. Rosmaster_R2 using the app to build maps
  • 9. Rosmaster_R2 navigating with the app
25. ROS2-OpenCV courses
  • 1. opencv basic course
  • 2. ROS+opencv application
  • 3. QR code creation and recognition
  • 4. AR Vision
  • 5. mediapipe fun gameplay
  • 6. Patrol line autopilot
26. ROS2-Depth camera courses
  • 1. Depth camera use
  • 2. Camera calibration
  • 3. Color tracking
  • 4. KCF object tracking
  • 5. ORB_SLAM2 Basics
  • 6. ORB_SLAM2 PCL mapping
  • 7. ORB_SLAM2 Octomap mapping
  • 8. RTAB-Map 3D mapping navigation
27.ROS2- Voice control courses
  • 0. How to use old voice module in new image
  • 1.1 Introduction to the module-New
  • 1.2 Voice Control Module Port Binding-New
  • 1.3 Introduction to the module-Old
  • 2. Voice control car movement
  • 3. Voice control autopilot
  • 4. Voice control color recognition
  • 5. Voice control color tracking
  • 6. Voice control multi-point navigation
28.Deep learning courses(SUPER)
  • 1.KNN recognizes handwritten digitsnew
  • 2.Basic use of TensorFlownew
  • 3.Basic use of PyTorch(jetson)new
  • 4.YOLOv11Model conversion(SUPER)new
  • 5.YOLOv11Dataset annotation(SUPER)new
  • 6.YOLOv11Model conversion + tensorrt acceleration(SUPER)new
  • 7.YOLOv11Object recognition(SUPER)new
29. ROS2-Multi-robot control
  • 1. Multi-robot control
  • 2. Multi-robot navigation
LLM tutorial
1.Development environment
  • 0. Model usage instructions
  • 1.Environments deployment
  • 2.Dialogue platform installation
2.Jetson Nano B01
  • 1.Qwen2 model
  • 2.TinyLlama model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.Orca Mini model
  • 6.StarCoder2 model
  • 7.DeepSeek-R1 model
  • 8.Expand LLaVA-Phi3
3.Jetson Orin NXNANO
  • 1.Llama3 model
  • 2.Qwen2 model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.WizardLM2 model
  • 6.Codellama model
  • 7.DeepSeek-R1 model
  • 8.Orca Mini model
  • 9.StarCoder2 model
  • 10.TinyLlama model
  • 11.Expand LLaVA
  • 12.Expand LLaVA-Phi3
4.Raspberry Pi 5B
  • 1.Meta AI Llama3 model
  • 2.Qwen2 model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.WizardLM2 model
  • 6.Meta AI Codellama model
  • 7.DeepSeek-R1 model
  • 8.Expand LLaVA
FAQ
  • 1.Using your own Jetson board, car cannot start normally
Download
  • RemoteCtrl_APP(iOS/Android)
  • Mapping_APP(iOS_Android)
  • Instruction Manual
  • SystemFile_ROS1
  • SystemFile_ROS2
  • SystemFile_ROS2_OrinNANOSUPER
  • SystemFile_ROS2_OrinNXSUPER
  • VM software
  • Code
  • Jetson_Boot_USB.tar.gz
  • Autopilot Annex
  • Other_Annex_File
  • LLM_SystemFile
  • ROS2_Basic_VM
Download ZIP

Welcome to ROSMASTER R2 repository

1. Multi-robot control

1. Multi-vehicle control

1. Program function description

Connect the handle to the virtual machine and set the virtual machine to connect to the handle. After the programs on the virtual machine and the car are started, you can control two cars at the same time through the handle, and the movements of the two cars are synchronized.

2. Program reference path

Raspberry Pi PI5 master control, you need to enter the docker container first, Orin motherboard does not need to enter,

The location of the function source code is

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~/yahboomcar_ros2_ws/yahboomcar_ws/src/yahboomcar_multi/launch

The file for virtual machine startup, the source code location is,

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~/yahboomcar_ros2_ws/yahboomcar_ws/src/yahboomcar_multi/yahboomcar_multi

3. Program startup

Note: Here you need to set up multi-machine communication in advance, that is, the virtual machine and the car (taking two cars as an example) need to be in the same LAN and the car ros environment, the virtual machine's ROS_DOMAIN_ID must be the same, in order to be able to perform distributed communication. Setting method reference: [06], Linux operating system -> [04], multi-machine communication configuration

3.1, startup command

** For Raspberry Pi PI5 master control, you need to enter the docker container of car 1 and car 2 respectively, but you do not need to enter the docker container of Orin motherboard.**

According to the actual model, enter in the terminal

#X3 model launch
#Car 1
ros2 launch yahboomcar_multi X3_bringup_multi_ctrl.launch.xml robot_name:=robot1
#Car 2
ros2 launch yahboomcar_multi X3_bringup_multi_ctrl.launch.xml robot_name:=robot2
#R2 model launch
#Car 1
ros2 launch yahboomcar_multi R2_bringup_multi_ctrl.launch.xml robot_name:=robot1
#Car 2
ros2 launch yahboomcar_multi R2_bringup_multi_ctrl.launch.xml robot_name:=robot2

#Virtual machine launch
#The handle program currently only supports the launch of the same model of car, X3 model
ros2 launch yahboomcar_multi X3_joy_ctrl.launch.py
#raspi5 master control execution
#ros2 run yahboomcar_ctrl yahboom_joy_X3
#The handle program currently only supports starting the car of the same model, R2 model
ros2 launch yahboomcar_multi R2_joy_ctrl.launch.py
#raspi5 main control execution
#ros2 run yahboomcar_ctrl yahboom_joy_R2

[robot_name] indicates the serial number of the vehicle to start. Currently, the program can choose to start robot1 and robot2.

3.2. View topic nodes

Enter the following command in the virtual machine terminal,

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ros2 topic list

image-20230727101808020

3.3. View the node communication diagram

Enter the following command in the virtual machine terminal,

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ros2 run rqt_graph rqt_graph

image-20230727101643106

It can be seen that the virtual machine published the topic speed of /cmd_vel, and the chassis of robot1 and robot2 have subscribed to the topic, so when the virtual machine publishes the topic data, both cars will receive it and then control the movement of their respective chassis.

4. Core code analysis

The code on the virtual machine side is the same as the handle control code on the car side. I won’t go into details here. We mainly look at the content of the car side and the startup.

The file takes the X3 car as an example. The startup file is X3_bringup_multi_ctrl.launch.xml.

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<launch>
<arg name="robot_name" default="robot1"/>
<group>
<push-ros-namespace namespace="$(var robot_name)"/>
<!--driver_node-->
<node name="driver" pkg="yahboomcar_bringup" exec="Mcnamu_driver_X3" output="screen">
             <param name="imu_link" value="$(var robot_name)/imu_link"/>
             <remap from="cmd_vel" to="/cmd_vel"/>
         </node>
<!--base_node-->
<node name="base" pkg="yahboomcar_base_node" exec="base_node_X3" output="screen">
<param name="odom_frame" value="$(var robot_name)/odom"/>
<param name="base_footprint_frame" value="$(var robot_name)/base_footprint"/>
</node>
<!--imu_filter_node-->
<node name="imu_filter" pkg="imu_filter_madgwick" exec="imu_filter_madgwick_node" output="screen">
<param name="fixed_frame" value="$(var robot_name)/base_link"/>
             <param name="use_mag" value="false"/>
             <param name="publish_tf" value="false"/>
             <param name="world_frame" value="$(var robot_name)/enu"/>
             <param name="orientation_stddev" value="0.05"/>
         </node>
         <!--ekf_node-->
         <node name="ekf_filter_node" pkg="robot_localization" exec="ekf_node">
             <param name="odom_frame" value="$(var robot_name)/odom"/>
             <param name="base_link_frame" value="$(var robot_name)/base_footprint"/>
             <param name="world_frame" value="$(var robot_name)/odom"/>
             <param from="$(find-pkg-share yahboomcar_multi)/param/X3_ekf_$(var robot_name).yaml"/>
             <remap from="odometry/filtered" to="odom"/>
             <remap from="/odom_raw" to="odom_raw"/>
         </node>
</group>
     <include file="$(find-pkg-share yahboomcar_description)/launch/description_X3_multi_$(var robot_name).launch.py"/>
</launch>

The xml format is used here to write the launch file, which facilitates us to add namespaces in front of multiple nodes. Adding namespace is to solve the conflict caused by the same node name. We have two cars here. Take the chassis program as an example. If both chassis nodes are named driver, then after establishing multi-machine communication, this will not work. It is allowed, so we add the namespace namespace before the node name. In this way, the chassis node name of car 1 is /robot1/driver, and the chassis node program of car 2 is /robot2/driver. In the launch file in XML format, a group is used to specify that within this group, both the node name and the topic name need to be added with namespace.

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<group>
<push-ros-namespace namespace="$(var robot_name)"/>
</group>

To reference the parameters defined in the launch file in XML format, use $(var robot_name). The parameter passed in here is robot_name. When entering the command, you can enter it in the command line.

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ros2 launch yahboomcar_multi robot_name:=robot1

One thing to note here is that after adding the namespace, we remapped the topic name of /robot1/cmd_vel to /cmd_vel in order to receive topic messages sent by the virtual machine.

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<node name="driver" pkg="yahboomcar_bringup" exec="Mcnamu_driver_X3" output="screen">
<param name="imu_link" value="$(var robot_name)/imu_link"/>
<remap from="cmd_vel" to="/cmd_vel"/>
</node>

Regarding the passing of parameters, adding the namespace needs to be stated in the launch file, such as the following parameters,

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<node name="base" pkg="yahboomcar_base_node" exec="base_node_X3" output="screen">
<param name="odom_frame" value="$(var robot_name)/odom"/>
<param name="base_footprint_frame" value="$(var robot_name)/base_footprint"/>
</node>

It can be seen that the odom_frame parameter is assigned to $(var robot_name)/odom, and the base_footprint_frame parameter is assigned to $(var robot_name)/base_footprint.

If some parameters do not require a namespace, then pass them in in the form of a parameter list, for example,

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<param from="$(find-pkg-share yahboomcar_multi)/param/X3_ekf_$(var robot_name).yaml"/>

What needs to be noted in this parameter table is that you need to add the namespace to find it accurately. If we start robot1, then the started node becomes robot1/ekf_filter_node, so the beginning of the parameter file should be,

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### ekf config file ###
robot1/ekf_filter_node:
ros__parameters:
YOLOv11Object recognition(SUPER)
Multi-robot navigation

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