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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

04. Multi-computer communication configuration

04. Multi-computer communication configuration

 

04. Multi-computer communication configuration4.1. Concepts4.2 Implementation4.2.1 Default implementation4.2.2. Distributed network grouping4.3 Notes4.4 Calculation rules for DDS domain ID values

The operating environment and hardware and software reference configuration are as follows:

  • Reference model: ROSMASTER X3
  • Robot hardware configuration: Arm series main control, Silan A1 Lidar, AstraPro Plus depth camera.
  • Robot system: Ubuntu (version not required) + docker (version 20.10.21 and above)
  • PC virtual machine: Ubuntu (20.04) + ROS2 (Foxy)
  • Usage scenario: use on a relatively clean 2D plane

 

4.1. Concepts

Multi-computer communication, i.e. distributed communication, is a communication strategy that allows data interaction between different hosts over a network.

ROS2 itself is a distributed communication framework, which can easily realize the communication between different devices. The middleware that ROS2 is based on is DDS, and when in the same network, distributed communication can be realized through the domain ID mechanism (ROS_DOMAIN_ID) of DDS, and the general process is: before starting a node, you can set the value of the domain ID, and different nodes can freely discover and communicate with each other if they have the same domain ID. are the same, then they can freely discover and communicate, and vice versa, if the domain ID values are different, it cannot be realized. By default, the domain ID used for all nodes to start up is 0. In other words, as long as you ensure that you are on the same network, you don't need to do any configuration for different nodes on different ROS2 devices to realize distributed communication.

Distributed communication is used in a wide range of scenarios, such as unmanned vehicle formations, drone formations, remote control, and so on, all of which rely on distributed communication for data interaction.

4.2 Implementation

 

4.2.1 Default implementation

Distributed communication is already realized by simply having the host and the slave [there can be more than one] in the same network. For example, the host and the slave are connected to the same WiFi or the same router.

The virtual machine in Windows is in the same network as the host by setting the network to [bridge mode].

 

Test:

1, the host side of the [cart] execution:

Demonstration here is the cart in docker, docker uses the network mode is host mode, host mode is simply and the cart share a network, so with the cart on the implementation of no difference.

xxxxxxxxxx
ros2 run demo_nodes_py talker
  1. while the slave side [VM] is executed:
xxxxxxxxxx
ros2 run demo_nodes_py listener

If the following is displayed: the topic published by the host can be subscribed to by the slave in time, it means that multi-computer communication has been realized

 

4.2.2. Distributed network grouping

Assuming that there are other robots in use in the network you are in now, in order not to be interfered by other robots, you can also set up a grouping for your robots.

ROS2 provides a DOMAIN mechanism, similar to grouping, in the same DOMAIN in the computer to communicate, we can be in the host side of the [trolley] and the slave side of the [virtual machine] of the .bashrc to add such a sentence in the configuration, you can assign the two to a group:

xxxxxxxxxx
$ export ROS_DOMAIN_ID=<your_domain_id>

If the IDs assigned to the host side [cart] and the slave side [VM] are different, the two cannot communicate for the purpose of grouping.

 

Test:

1, the host side [cart] execution:

Demonstrated here is the cart is in docker, docker uses the network mode is host mode, host mode is simply and the cart share a network, so with the cart on the implementation of no difference.

xxxxxxxxxx
echo "export ROS_DOMAIN_ID=6" >> ~/.bashrc  # 这里的6是ROS_DOMAIN_ID, 不一定要用6,符合ROS_DOMAIN_ID的规则即可
# The 6 here is the ROS_DOMAIN_ID, it doesn't have to be a 6, just the ROS_DOMAIN_ID rule.
source ~/.bashrc
ros2 run demo_nodes_py talker
  1. while the slave side [VM] is executed:
xxxxxxxxxx
echo "export ROS_DOMAIN_ID=6" >> ~/.bashrc  # 这里和主机端的值保持一致
# It's consistent with the values on the host side
source ~/.bashrc
ros2 run demo_nodes_py listener

If the following is displayed: the topic posted by the host can be subscribed to by the slave in time, it means that grouped multi-computer communication has been realized

image-20230423151246730-1683341857526-2

 

4.3 Notes

The value of ROS_DOMAIN_ID is not arbitrary, there are some constraints:

  1. It is recommended that the value of ROS_DOMAIN_ID is between [0,101], including 0 and 101;
  2. the total number of nodes within each domain ID is limited and needs to be less than or equal to 120;
  3. if the domain ID is 101, then the total number of nodes in the domain needs to be less than or equal to 54.

 

4.4 Calculation rules for DDS domain ID values

The rules related to the calculation of the domain ID value are as follows:

  1. DDS is based on TCP/IP or UDP/IP network communication protocol, network communication needs to specify the port number, which is represented by a 2-byte unsigned integer and its value range is between [0,65535];
  2. The allocation of port number also has its own rules, not arbitrary use, according to the DDS protocol to 7400 as the starting port, that is, the port can be used for [7400,65535], and is known in accordance with the DDS protocol by default, each domain ID occupies 250 ports, then the number of domain ID: (65535-7400)/250 = 232 (a), corresponding to the range of values is [0,65535], and its value range is [0,65535]. The number of domain IDs is: (65535-7400)/250 = 232 (ports), which corresponds to a range of [0,231];
  3. The operating system will also set up some reserved ports, when using ports in the DDS, you also need to avoid these reserved ports, so as to avoid conflicts in the use of different operating systems reserved ports and there are differences in the end result is that, in Linux, the available domain ID [0,101] and [215-231], in Windows and Mac available domain ID [0, 166], in summary, the available domain ID [0, 166], the available domain ID [0, 166], the available domain ID [0, 166], the available domain ID [0, 166], the available domain ID [0, 166]. 166]. In summary, for compatibility with multiple platforms, it is recommended that the domain IDs take values in the range of [0,101]. 4.
  4. Each domain ID occupies 250 ports by default, and each ROS2 node needs to occupy two ports. In addition, according to the DDS protocol within the port segment of each domain ID, the 1st and 2nd ports are Discovery Multicast ports and User Multicast ports, and the 11th and 12th ports are the Discovery Unicast ports and User Multicast ports for the first node of the domain, and the 11th and 12th ports are the Discovery Unicast ports and User Multicast ports for the first node of the domain. Discovery Unicast port and User Unicast, and the ports occupied by the subsequent nodes are in order, then the maximum number of nodes in a domain ID is: (250-10)/2 = 120 (pcs);
  5. Special case: when the domain ID value is 101, the second half of its ports belong to the reserved ports of the operating system, and the maximum number of its nodes is 54.

The above calculation rules can be understood.

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