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ROSMASTER M3 PRO📖
0.Configuration and Operation Guide
  • 1. Quick start handle to control the car
  • 2. Log in to the car and view the code
  • 3. Robotic Arm Calibration
  • 4. Enter the Docker (Jetson-Nano and Raspberry Pi 5 users, see here)
  • 5. Assembly video
  • 6. Modify the firmware parameters of the car control board
  • 7. Frequently Asked Questions and Precautions
  • 8. Precautions for DIY Robotic Arm
1.Chassis Control Course
  • 1.ROS control
  • 2.Handle control
  • 3.Keyboard control
  • 4.Angular velocity calibration
  • 5.Line velocity calibration
  • 6.Line patrol automatic driving
  • 7.Patrol
2.Lidar Course
  • 1.Lidar introduction and use
  • 2.Dual Lidar fusion
  • 3.Lidar obstacle avoidance
  • 4.Lidar tracking
  • 5.Lidar guard
  • 6.Gmapping-SLAM mapping
  • 7.Cartographer-SLAM mapping
  • 8.slam_toolbox mapping
  • 9.Navigation2 single-point navigation avoid
  • 10.Navigation2 multi-point navigation avoid
  • 11.Repositioning navigation
  • 12.RTAB-Map mapping
  • 13.RTAB-Map navigation
  • 14.APP mapping navigation
  • 15.Machine code handling
  • 16.Color block transport
  • 17.Navigation via Pose-Constrained Visual Relocalizationnew
3.Depth Camera Course
  • 1.Dabai_DCW2 camera introduction
  • 2.Depth pseudo-color image
  • 3.Depth camera distance measurement
  • 4.Wood block volume measurement
  • 5.Mediapipe gesture recognition
  • 6.Edge detection
  • 7.YOLOv8 object detection
  • 8.Deep learning object tracking
  • 9. Transformer Model Tracking Algorithmnew
4.Robotic Arm and 3D Space Gripping Course
  • 1.Robotic arm solution
  • 2.Robotic arm chassis linkage control
  • 3.Machine code ID sorting
  • 4.Sorting height abnormality machine code
  • 5.Tracking and gripping machine code
  • 6.Color block color sorting
  • 7.Sorting height abnormality color block
  • 8.Tracking and gripping color block
  • 9.Wood block shape sorting
  • 10.KCF tracking and gripping objects
  • 11.Medipipe gesture ID sorting machine code
  • 12.Mediapipe gesture height sorting machine code
  • 13.Desktop tracking and gripping machine code
  • 14.3D tracking machine code
  • 15.Line patrol and obstacle removal
5.Road network planning and navigationnew
  • 1. Introduction To Road Network Planning
  • 2. Build A Pose Map
  • 3. Road Network Annotation
  • 4. Planning And Navigation Between Waypoints
  • 5. Road Network Navigation In Any Pose
  • 6. Path Re-planning
6.OpenClaw Basic Coursenew
  • 1. Introduction to OpenClaw
  • 2. OpenClaw Core Concepts
  • 3. OpenClaw API-KEY Configuration
  • 4. OpenClaw Switch Models
  • 5. OpenClaw System Prompt Words
  • 6. OpenClaw Common CLI Commands
7.OpenClaw Interaction Methodnew
  • 1. OpenClaw Webchat Interaction
  • 2. OpenClaw Tui Interaction
  • 3. OpenClaw Voice Dialogue Interaction
  • 4. OpenClaw WhatsApp Interaction
8.OpenClaw Developmentnew
  • 1. OpenClaw connects to the MCP interface of the robot
  • 2. Robot CLI Command Tool
  • 3. Robot control plugin tool
  • 4. Reply bridge plugin tool
  • 5. OpenClaw multimodal vision
  • 6. OpenClaw chassis control
  • 7. OpenClaw robotic arm control
  • 8. OpenClaw skills development
  • 9. OpenClaw timed tasks
  • 10. OpenClaw multi-agent intelligent agent
  • 11. OpenClaw active interaction
  • 12. OpenClaw vector memory
9.OpenClaw Embodied intelligent applicationnew
  • 1. OpenClaw target tracking
  • 2. OpenClaw robotic arm tracking and grasping
  • 3. OpenClaw robotic arm fixed-point placement
  • 4. OpenClaw garbage sorting
  • 5. OpenClaw slam mapping and navigation
  • 6. OpenClaw navigation transfer
  • 7. OpenClaw machine code clip
  • 8. OpenClaw color line patrol
  • 9. OpenClaw visual distance measurement
10.OpenClaw scenario sandboxnew
  • 1. Map description and prop placement
  • 2. Build sand table map
  • 3. Visual relocation markers
  • 4. Map mapping markers
  • 5. OpenClaw scenario sandbox comprehensive case
11.AI Model Basics
  • 1.AI large model types and principles
  • 2.RAG retrieval enhancement and model training samples
  • 3.Embodied intelligent robot system architecture
  • 4.Embodied intelligent functions core source code
12.AI Model Development
  • 01.Register a model service provider account
  • 02. Configuring API-KEY
  • 03. Introduction to Dify
  • 04. Basic Dify Features
  • 05. AI Large Model Development - chatbot
  • 06. Deploy the RAG knowledge base
  • 07. RAG knowledge base + chatbot
  • 08. AI agent workflow
  • 09. Custom wake-up response
  • 10. Core module testing tools
13.AI Large Model (Text Version)
  • 1.Semantic understand instruction following
  • 2.Multimodal visual understand
  • 3.Multimodal visual understand+robotic arm grab
  • 4.Multimodal visual understand+SLAM navigation
  • 5.Robotic arm grab+Multimodal visual understand+SLAM navigation
  • 6.Intention estimation
14.AI Large Model(Voice Version)
  • 1.Semantic understand instruction following
  • 2.Multimodal visual understand
  • 3.Multimodal visual understand+robotic arm grab
  • 4.Multimodal visual understand+SLAM navigation
  • 5.Robotic arm grab+Multimodal visual understand+SLAM navigation
  • 6.Intention estimation
15.Mediapipe Visual Course
  • 1.Hand detection
  • 2.Posture detection
  • 3.Overall detection
  • 4.Facial Landmark Detection
  • 5.Face detection
  • 6.Face special effects
  • 7.3D object recognition
  • 8.Brush
  • 9.Finger control
  • 10.Palm target positioning
  • 11.Fingertip trajectory recognition
  • 12.Fingertip gesture control robotic arm
  • 13.Gesture grabbing and releasing objects
  • 14.Finger control robotic arm
  • 15.Medipipe gesture control robotic arm action group
16.MoveIt2 Simulation Course
  • 1.MovelT2 configuration
  • 2.MovelT2 simulation-reality linkage
  • 3.Random movement
  • 4.Forward kinematics design
  • 5.Inverse kinematics design
  • 6.Cartesian path
  • 7.Trajectory planning
  • 8.Collision detection
  • 9.Scene design
17.Multi-vehicle Course
  • 1.Multi-vehicle chassis control
  • 2.Multi-vehicle robotic arm control
  • 3.Multi-vehicle navigation
  • 4.Multi-vehicle formation
18.Control Board Course
  • 1.Development environment setup
  • 2.Control board STM32 basic routine
  • 3.Control board micro_ros basic routine
19.Docker Course
  • 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
20.Image Processing Basics Course
  • 1. Introduction to Open Source CV
  • 2. Image reading and display
  • 3. Image writing
  • 4. Image quality
  • 5. Pixel Operation
  • 6. Image zoom
  • 7. Image cutting
  • 8. Image translation
  • 9. Image Mirroring
  • 10. Affine Transformation
  • 11. Image Rotation
  • 12. Perspective Transformation
  • 13. Grayscale processing
  • 14. Image Binarization
  • 15. Edge Detection
  • 16. Line drawing
  • 17. Rectangle and circle drawing
  • 18. Drawing text and pictures
21.Main Control Course
Jetson Nano B01
  • 1. Introduction to the Jetson Nano B01 SUB Board
  • 2. Burn the system image
  • 3. Re-read the memory card or USB drive that has been burned
  • 4. Startup system
  • 5. Jetson Nano B01 System and Desktop Introduction
  • 6. Memory card or USB flash drive expansion
  • 7. Network Configuration
  • 8. SSH remote login & file transfer
  • 9. VNC Remote Login
  • 10. Jetson Nano B01 system backup
  • 11. Jetson Nano Swap space increased
  • 12. Installation and use of Jtop
Jetson Orin Nano_NX
  • 1.Jetson Orin board introduction
  • 2.Restore the factory image system
  • 3.Backup SSD system
  • 4.SSD expansion
  • 5.Network configuration
  • 6.SSH remote login
  • 7.VNC remote control
  • 8.Remote file transfer
  • 9.Jtop tool
  • 10.Exchange space expansion
Raspberry Pi
  • 1. Introduction to Raspberry PI 5
  • 2. Raspberry PI system installation and backup
  • 3. Powering the Raspberry PI 5
  • 4. Startup of Raspberry PI 5
  • 5. Update and upgrade operating system
  • 6. Introduction to raspi-config tool
  • 7. config.txt file description
  • 8. Network Configuration
  • 9. remote access
  • 10. Transfer files remotely
  • 11. Set display resolution and rotation
  • 12. Set screen to sleep
  • 13. Play audio and video
  • 14. Using USB camera
  • 15. Using MIPI camera
  • 16. Get real-time temperature of Raspberry Pi
22.Linux System Course
  • 1.Introduction to Linux system
  • 2.Ubuntu file system
  • 3.Ubuntu common commands
  • 4.Ubuntu common editors
  • 5.Ubuntu software operation commands
  • 6.Virtual machine installation
  • 7.SSH remote control
  • 8.VNC remote control
  • 9.Transfer files remotely
  • 10.Driver library and communication
  • 11.Static IP and hotspot mode
  • 12.Bind device ID
  • 13.Capacity expansion and resource allocation
  • 14.Update system software sources
  • 15.Set root user password
  • 16.sudo free password
  • 17.Connect to WiFi network
  • 18.View system version
  • 19.Customized service management
  • 20.Back up system image
23.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
Download
  • Mapping_APP(iOS_Android)
  • Robot_Image_System_File
  • Code-Firmware
  • Instruction_Manual
  • VM_File
  • Software_Tools
  • Firmware_DriverFile
  • 3D_Model_File
  • ROS2_Basic_VM
  • Other_Annex
Download ZIP

Welcome to ROSMASTER M3 PRO repository

3、Docker images deeply understand and publish images

3、Docker images deeply understand and publish images

 

3、Docker images deeply understand and publish images3.1、image understanding3.2、UnionFS(Federated file systems)3.3、image layering3.3.1、hierarchical understanding3.3.2、Docker images should use layering benefits3.4、Make and publish images3.4.1、Make an image3.4.2、Publish the image

The operating environment and software and hardware reference configurations 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

3.1、image understanding

  1. An image is a lightweight, executable stand-alone software package that contains everything needed to run a piece of software. We package applications and configurations into a ready, deliverable, deployable runtime environment, including code, libraries, environment variables and configuration files required for runtime, and this large package runtime environment is the image image file.

  2. Docker container instances can only be generated through image files.

3.2、UnionFS(Federated file systems)

1.Union file system (UnionFS) is a hierarchical, lightweight, high-performance file system, it is the basis of docker images, and supports the modification of the file system as a commit to overlay layer by layer, while different directories can be mounted under the same virtual file system.

2.The image can be inherited through layering, and based on the basic image, various specific application images can be made.

Features of the Union file system: load multiple file systems at the same time, but from the outside, only one file system can be seen; Federated loading overlays the layers of file systems so that the final file system contains files and directories for all layers.

3.3、image layering

When downloading an image, pay attention to the downloaded log output, you can see that it is downloading layer by layer:

image-20230424154810939

# The way to view image layering can be done with the command: docker image inspect image name
jetson@ubuntu:~$ docker image inspect mysql:latest
[
    {
        "Id": "sha256:5371f8c3b63eec64a33b35530be5212d6148e0940111b57b689b5ba1ffe808c8",
        .........
        "RootFS": {
            "Type": "layers",
            "Layers": [
                "sha256:d6d4fc6aef875958d6186f85f03d88e6bb6484ab2dd56b30a79163baceff2f6d",
                "sha256:05c3b0b311a02bc56ca23105a76d16bc9b8c1d3e6eac808f4efb1a2e8350224b",
                "sha256:7b80f7f05642477ebc7d93de9539af27caab7c41a768db250fe3fe2b5506ca2c",
                "sha256:50e037faefab22cb1c75e60abb388b823e96a845650f3abd6d0a27e07a5a1d5e",
                "sha256:66040abb3f7201d2cc64531349a8225412db1029447a9431d59d999c941d56f6",
                "sha256:857162425652837a362aa5f1c3d4974cc83702728793de52ba48176d5367a89b",
                "sha256:7eebed3016f6b6ab68aa8e6be35f0689a3c18d331b7b542984a0050b859eaf26",
                "sha256:2fc4c142633d57d795edc0f3fd457f99a35fa611eab8b8c5d75c66e6eb729bc2",
                "sha256:7fde2d12d484f0c14dabd9ca845da0bcdaf60bd773a58ca2d73687473950e7fe",
                "sha256:9319848a00d38e15b754fa9dcd3b6e77ac8506850d32d8af493283131b9745a3",
                "sha256:5ff94d41f068ea5b52244393771471edb6a9a10f7a4ebafda9ef6629874a899b"
            ]
        },
        "Metadata": {
            "LastTagTime": "0001-01-01T00:00:00Z"
        }
    }
]

3.3.1、hierarchical understanding

  • All docker images start from a base image layer, and when modifications or additions are made, a new image layer will be created on top of the current image layer.

  • For a simple example, if a new image is created based on Ubuntu 20.04, this is the first layer of the new image; If you add a Python package to the image, a second image layer is created on top of the base image layer; If you continue to add a security patch, a third mirror layer is created.

  • Docker images are all read-only, and when the container starts, a new writable layer is loaded on top of the image! This layer is what we usually call the container layer, and what is under the container is called the image layer!

3.3.2、Docker images should use layering benefits

Resource sharing, for example, if there are multiple images built from the same base image, then the host only needs to keep a base image on disk, and only one base image needs to be loaded in memory, so that all containers can be served, and each layer of the image can be shared.

3.4、Make and publish images

3.4.1、Make an image

Method 1: Submit an image from the container:

​x
# command
docker commit -m="description of commit" -a="author" container id Target image name to be created: [tag name] [You can also omit the -m -a parameter]

# Test
jetson@ubuntu:~$ docker ps -a
CONTAINER ID   IMAGE           COMMAND       CREATED       STATUS                   PORTS     NAMES
c54bf9efae47   ubuntu:latest   "/bin/bash"   3 hours ago   Up 24 minutes                      funny_hugle
3b9c01839579   hello-world     "/hello"      3 hours ago   Exited (0) 3 hours ago             jovial_brown
jetson@ubuntu:~$ docker commit c54bf9efae47 ubuntu:1.0
sha256:78ca7be949b6412f74ba12e8d16bd548aaa7c3fa25134326db3a67784f848f8f
jetson@ubuntu:~$ docker images   # Generated the ubuntu:1.0 image
REPOSITORY                   TAG       IMAGE ID       CREATED         SIZE
ubuntu                       1.0       78ca7be949b6   5 seconds ago   69.2MB
yahboomtechnology/ros-foxy   3.4.0     49581aa78b6b   5 hours ago     24.3GB
yahboomtechnology/ros-foxy   3.3.9     cefb5ac2ca02   4 days ago      20.5GB
yahboomtechnology/ros-foxy   3.3.8     49996806c64a   4 days ago      20.5GB
yahboomtechnology/ros-foxy   3.3.7     8989b8860d17   5 days ago      17.1GB
yahboomtechnology/ros-foxy   3.3.6     326531363d6e   5 days ago      16.1GB
ubuntu                       latest    bab8ce5c00ca   6 weeks ago     69.2MB
hello-world                  latest    46331d942d63   13 months ago   9.14kB

Method 2: Make an image from a dockerfile:

xxxxxxxxxx
# command
docker build -f dockerfile file path -t new image name: TAG .  # The docker build command has a .     Represents the current directory
# Test
docker build -f dockerfile-ros2 -t yahboomtechnology/ros-foxy:1.2 .

For more information on writing dockerfiles, please refer to: https://docs.docker.com/develop/develop-images/dockerfile_best-practices/

3.4.2、Publish the image

The docker repository is a centralized storage place for image files. The largest public repository is Docker Hub (https://hub.docker.com/), which houses a huge number of images for users to download. Domestic public warehouses include Alibaba Cloud, NetEase Cloud, etc.

Steps to publish the image to docker hub:

  1. Address: https://hub.docker.com/, register an account first

  2. Ensure that the account can log in normally

image-20230424151714735

  1. Use the tag command to modify the image name

The specification for publishing an image to docker hub is:

xxxxxxxxxx
docker push registration username/image name

For example, my registered username here is: pengan88, then you must first change the image name

xxxxxxxxxx
# Command:
The name of the image after the docker tag image ID is modified

# Test
jetson@ubuntu:~$ docker images
REPOSITORY                   TAG       IMAGE ID       CREATED         SIZE
ubuntu                       1.0       78ca7be949b6   5 seconds ago   69.2MB
ubuntu                       latest    bab8ce5c00ca   6 weeks ago     69.2MB
hello-world                  latest    46331d942d63   13 months ago   9.14kB
jetson@ubuntu:~$ docker tag 78ca7be949b6 pengan88/ubuntu:1.0
jetson@ubuntu:~$ docker images
REPOSITORY                   TAG       IMAGE ID       CREATED          SIZE
pengan88/ubuntu              1.0       78ca7be949b6   23 minutes ago   69.2MB
ubuntu                       1.0       78ca7be949b6   23 minutes ago   69.2MB
ubuntu                       latest    bab8ce5c00ca   6 weeks ago      69.2MB
hello-world                  latest    46331d942d63   13 months ago    9.14kB
  1. Log in to Docker Hub to publish the image:

xxxxxxxxxx
jetson@ubuntu:~$ docker login -u pengan88
Password:     # Enter the password of the account registered by Docker Hub here
WARNING! Your password will be stored unencrypted in /home/jetson/.docker/config.json.
Configure a credential helper to remove this warning. See
https://docs.docker.com/engine/reference/commandline/login/#credentials-store

Login Succeeded
jetson@ubuntu:~$ docker push pengan88/ubuntu:1.0
The push refers to repository [docker.io/pengan88/ubuntu]
ca774712d11b: Pushed
874b048c963a: Mounted from library/ubuntu
1.0: digest: sha256:6767d7949e1c2c2adffbc5d3c232499435b95080a25884657fae366ccb71394d size: 736

5、Visit Docker Hub to see that it has been successfully released

image-20230424152530278

Common commands for docker image containers
Docker hardware interaction and data processing

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