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ROSMASTER X3📖
1.About ROSMASTER X3
  • 1.1 Wiring Introduction
  • 1.2 Precautions for battery
  • 1.3 First Trial
2.Assembly steps
  • Installation Video(1-10)
  • Installation Video(11-18)
  • Installation Video(20-28)
  • Installation Video(29-30)
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
  • 12.1 Lidar basic-SLAM
  • 12.1 Lidar basic-4ROS
  • 12.2 Lidar avoiding
  • 12.3 Lidar guard
  • 12.4 Lidar follow
  • 12.5 Patrol game
  • 12.6 gmapping mapping algorithm
  • 12.7 hector mapping algorithm
  • 12.8 karto mapping algorithm
  • 12.9 cartographer mapping algorithm
  • 12.10 rrt_exploration mapping algorithm
  • 12.11 AMCL
  • 12.12 Navigation and avoiding
  • 12.13 APP mapping and navigation
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 control
  • 2. Model aircraft control
  • 3. Wireless Handle Control Tutorial
18.ROS2- Hardware course
  • 1. About expansion board_V1.0
  • 1. About expansion board_V3.0
  • 2. STM32 Development environment
  • 3. Button control
  • 4. FreeRTOS application
  • 5. Serial communication
  • 6. SBUS model aircraft remote control
  • 7. CAN bus communication
  • 8. RGB colorful light bar
  • 9. Timer interrupt to control PWM servo
  • 10. Control serial port servos
  • 11. Nine-axis attitude sensor to obtain data
  • 12. Control motor
  • 13. Timer captures the encoder data
  • 14. Robot kinematics analysis theory
  • 15. PID control robot movement
19.ROS2- ROSMASTER basic course
  • 1. Update the firmware
  • 2. Turn off the self-starting process at startup
  • 3. Install the Rosmaster driver library
  • 4. Buzzer whistle
  • 5. Control PWM servo
  • 6. RGB colorful light bar special effects display
  • 7. Control motor
  • 8. Control robot movement
  • 9. Control Serial Servo
20.ROS2- Linux operating systemnew
  • 1. Virtual machine installation and use
  • 2. Linux basics
  • 3. Remote control
  • 4. Multi-machine communication configuration
  • 5. Static IP and hotspot mode
  • 6. Bind the device ID
  • 7. Web page real-time monitoring
  • 8. Expansion tutorial
  • 9.1 Jetson Nano write sytem
  • 9.2 Raspberry Pi write system
  • 9.3 Orin series write system
  • 10.Jetpack old system upgraded to SUPER systemnew
21.ROS2- Docker(Nano Pi)
  • 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. Entering the Docker Container of the Robot
  • 6. Building a Robot Development Environment in Docker
  • 7. Method for customers to update 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- Depth camera course
  • 1.Depth camera usage
  • 2. Camera internal reference 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
25.ROS2- Lidar course
  • 1. Introduction and Use of Lidar
  • 2. Lidar avoiding
  • 3. Lidar follow
  • 4. Lidar guard
  • 5. Patrol game
  • 6. Gmapping mapping algorithm
  • 7. Cartographer mapping algorithm
  • 8. Navigation and obstacle avoidance
  • 9. Rosmaster_ X3 conducts mapping through the APP
  • 10. Rosmaster_ X3 Navigation through APP
26.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、line patrol automatic driving
27.ROS2- Voice control courses
  • 0.How to use old voice module in new image
  • 1. Introduction of voice module-new
  • 2. Voice control module port binding-new
  • 1. Introduction of voice module and port binding-old
  • 3. Voice control car movement
  • 4. Voice control Autopilot
  • 5. Voice control color recognition
  • 6. Voice control color tracking
  • 7. 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, ROSMASTER X3 cannot start normally
Download
  • RemoteCtrl_APP(Android/iOS)
  • Mapping_APP(iOS_Android)
  • Instruction Manual
  • SystemFile_ROS2
  • SystemFile_ROS1
  • SystemFile_ROS2_OrinNANOSUPER
  • SystemFile_ROS2_OrinNXSUPER
  • Code
  • Jetson_Boot_USB.tar.gz
  • VM software
  • Autopilot Annex
  • Other_Annex_File
  • LLM_SystemFile
  • ROS2_Basic_VM
Download ZIP
FAQ
  • 1、How to connect OLED?

Welcome to ROSMASTER X3 repository

6.9.2 Jetson Xavier NX write system

9.2 Jetson Xavier NX write system

9.2 Jetson Xavier NX write system1. View NVME SSD information 2. Prepare the L4T programming package 3. Modify system data 4. build a system image 5. Replace the IMG file of the system 6. Enter the flash mode 7. start brushing

Since the EMMC capacity of the Jetson NX motherboard is too small, it is necessary to burn the system to the SSD solid state drive.

1. View NVME SSD information

Before restoring the system to the solid state drive, you need to check the information of the solid state drive to be restored. Please insert the NVME solid state drive into the SSD socket of the Jetson Xavier NX, and power on the Jetson Xavier NX, open the terminal, and enter the following command to view the information.

sudo fdisk -l /dev/nvme0n1

img

Record the three data in the red box in the figure below. The first data indicates the capacity of the SSD, the second data indicates how many sectors (num_sectors: 250069680), and the third data indicates the words occupied by each sector. The number of sections (sector_size: 512).

2. Prepare the L4T programming package

  1. Download the file

Go to NVIDIA official website to download Jetson Xavier NX system L4T firmware:

https://developer.nvidia.com/embedded/linux-tegra-r3261

To download the latest version of the firmware, you need to download the Jetson Xavier NX-related L4T Driver Package[BSP], Sample Root Filesystem and Jetson Platform Fuse Burning and Secure Boot Documentation and Tools to the local.

img

image-20220518144542557

For example: I create a new jetsonNX folder in the virtual machine Ubuntu18.04 system, and download the file to the jetsonNX directory here. Right-click on the blank space to open the terminal.

img

  1. Unzip the file, note that sudo cannot be omitted here, otherwise it will affect the subsequent installation, the file is relatively large, and the unzipping time may take a few minutes.

Enter the following command to decompress.

​x
tar xf Jetson_Linux_R32.6.1_aarch64.tbz2 

sudo tar xf Tegra_Linux_Sample-Root-Filesystem_R32.6.1_aarch64.tbz2 -C ./Linux_for_Tegra/rootfs/ 

sudo tar xf secureboot_R32.6.1_aarch64.tbz2  

img

  1. Install the qemu file and enter y to confirm the installation.
xxxxxxxxxx
sudo apt-get install qemu-user-static 

img

  1. Generate binary files

First enter the following command to enter the Linux_for_Tegra folder, and run the command to generate the binary file.

xxxxxxxxxx
cd Linux_for_Tegra 

sudo ./apply_binaries.sh  

img

When you see the final success, it means OK.

img

3. Modify system data

xxxxxxxxxx
vim ./tools/kernel_flash/flash_l4t_nvme.xml 

img

Press i to enter the edit mode, and then replace the data of sector_size and num_sectors queried in the first step.

img

After the modification is completed, press the ESC key to exit the editing mode, then enter :wq and press the Enter key to save and exit.

4. build a system image

  1. Build the qspi startup component

Execute the following commands in the Linux_for_Tegra directory

xxxxxxxxxx
sudo ./tools/kernel_flash/l4t_initrd_flash.sh --no-flash jetson-xavier-nx-devkit-qspi internal 

img

  1. Build the system image

Execute the following commands in the Linux_for_Tegra directory

xxxxxxxxxx
sudo ./tools/kernel_flash/l4t_initrd_flash.sh --no-flash --external-device nvme0n1p1 -c ./tools/kernel_flash/flash_l4t_nvme.xml -S 118GiB --showlogs jetson-xavier-nx-devkit-emmc nvme0n1p1 

img

Explanation of the above parameters:

--no-flash: Indicates that the system is only compiled and not burned.

--external-device nvme0n1p1: Indicates burning to the /dev/nvme0n1p1 device, that is, the APP partition of the SSD.

-c ./tools/kernel_flash/flash_l4t_nvme.xml: Specify the burned xml file, that is, the file modified in the third step.

-S 118GiB: Indicates the size of the space occupied by the system APP partition. This value is the SSD capacity queried in the first step -1. Since the actual capacity of the SSD used this time is only 119.2GiB, the system also needs to reserve 1GiB space for other partitions, so the APP can occupy 118GiB.

--showlogs: Indicates that LOG information is displayed.

jetson-xavier-nx-devkit-emmc nvme0n1p1: Indicates that the Jetson Xavier NX device and the nvme0n1p1 partition are burned.

img

Finally, seeing Success indicates that the system was successfully built.

5. Replace the IMG file of the system

  1. Go to the factory image in the data to download the latest version of the image system compressed package file, and then decompress to get the img image file.
  2. Enter the Linux_for_Tegra directory
  3. Copy the original system file img as a backup (in order to save space, no backup can be made)
xxxxxxxxxx
sudo cp tools/kernel_flash/images/external/system.img tools/kernel_flash/images/external/system.img.bak 

 

  1. Copy and overwrite the system.img system file Copy the nx_rootfs.img file generated in the previous step to the external/ directory and overwrite the system.img file.
xxxxxxxxxx
sudo cp bootloader/nx_rootfs.img tools/kernel_flash/images/external/system.img 

img

Among them, bootloader/nx_rootfs.img is the path of the downloaded factory image file. It is modified according to the actual path. The name has been modified in advance to nx_rootfs.img. Note that the name cannot be in Chinese.

6. Enter the flash mode

  1. Jetson Xavier NX enters the system REC flashing mode.

Connect the jumper caps to the FC REC and GND pins, that is, to the second and third pins of the carrier board below the core board, as shown in the image below:

img

  1. Connect the line, connect the HDMI display, mouse, keyboard and microUSB data cable to the Jetson NX, and finally plug in the power supply. Since the jumper cap has been connected to the FC REC and GND pins in the previous step, it will automatically enter the REC flashing mode after power on.

img

Note here that using a virtual machine requires setting the device to connect to the virtual machine.

img

7. start brushing

Open a terminal and execute the following commands in the Linux_for_Tegra directory:

xxxxxxxxxx
sudo ./tools/kernel_flash/l4t_initrd_flash.sh --flash-only --external-device nvme0n1p1 -c ./tools/kernel_flash/flash_l4t_nvme.xml -S 118GiB --showlogs jetson-xavier-nx-devkit-emmc nvme0n1p1 

img

Note: After starting to burn the system, Jetson Xavier NX will restart again. If you are using a virtual machine, you need to manually connect Jetson Xavier NX to the virtual machine, otherwise it will fail to connect and exit the programming over time.

img

After the programming is complete, the Jetson Xavier NX will automatically power on.

Note: After programming the system, please unplug the jumper caps of FC REC and GND.

If you need to burn the backup system later, you can start from the fifth step.

Jetson Nano write sytem
Jetson TX2 NX write system

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