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DOFBOT-JetsonNANO📖
00.Must Read Before Use!!
  • 00.Must Read Before Use!!
01.First Trial
  • 1.First Trial
  • 2.Analysis of common problems
  • 3.Calibration offset
  • 4.Precautions for DIY Robotic Arm
  • 5.Jetson Nano Version – Must Read
  • 6.Robotic arm gripping anomaly solutions
02.Assemble Course
  • 1.Installation video
  • 2.Calibrate the Robotic Arm
  • 3.Install the map
03.Remote control course
  • 1.Mobile APP control
  • 2.USB handle control
  • 3.PC web page programming
04.Preparation
  • 1.Manage APP control service
  • 2.Manage JupyterLab service
  • 3.Manage OLED service
  • 4.Modifying ROS_DOMAIN_ID for Multi-Machine
  • 5.Jetpack old system upgraded to SUPER system
05.Basic control course
  • 1.Control RGB light
  • 2.Control buzzer
  • 3.Control single servo
  • 4.Read servo angle
  • 5.Control all servo
  • 6.DOFBOT up down left right
  • 7.DOFBOT dancing
  • 8.DOFBOT memory action
  • 9.DOFBOT grab block
  • 10.Porter
  • 11.Stacked Arhat
  • 12.Synchronous action
  • 13.USB camera display
06.AI vision basic course
  • 1.Gesture Recognition
  • 2.Color threshold adjustment&Color calibration
  • 3.Color recognition
  • 4.Face recognition
  • 5.YOLOv11 garbage recognition
  • 6.YOLOv11 object recognition
07.2D Visual Tracking Course
  • 1.PID algorithm basics
  • 2.Color block positioning
  • 3.Color block tracking
  • 4.Face positioning
  • 5.Face tracking
  • 6.Gesture recognition fixed action
08.2D Visual Grasping Course
  • 1.Gesture recognition stack blocks
  • 2.Color recognition grab blocks
  • 3.Catch game
  • 4.Color sorting and stacking
  • 5.Garbage sorting
  • 6.Color interaction
09.Mediapipe course
  • 1.Hand detection
  • 02.Posture detection
  • 3.Overall detection
  • 4.Facial Detection
  • 5.Face Detection
  • 6.Face effects
  • 7.3D object recognition
  • 8.Paintbrush
  • 9.Finger control
  • 10.Gesture Recognition
  • 11.Gesture control robotic arm action group
  • 12.Arm posture control robotic arm
  • 13.Palm Targeting
  • 14.Robotic arm tracks the palm
  • 15.Fingertip trajectory recognition
  • 16.Fingertip trajectory control robotic arm
  • 17.Gesture Grasp and Release Objects
  • 18.Finger Control Robot Arm
10.AI Large Model Voice Module (Must Read)new
  • 1. Introduction to AI Large Model Voice Module
  • 2. Flash the firmware (Must read)
  • 3. Modify the wake-up word and command word
11.2D Voice Control Coursenew
  • 01.Simple Voice Control
  • 02.Smart Voice Control
  • 03.Voice Action Control
  • 04.Memory Learning Mode
  • 05.Color Recognition with Voice Broadcast
  • 06.Color Recognition and Grasping with Voice Broadcast
  • 07.Color Recognition and Sorting with Voice Broadcast
  • 08.Voice Recognition Target Tracking
  • 09.Voice Control Stacking
  • 10.Voice Control Color Sorting and Stacking
  • 11.Garbage Recognition with Voice Broadcast
  • 12.Garbage Sorting with Voice Broadcast
12.Robotic Arm Control and Inverse Kinematics
  • 1. Robotic arm ROS control
  • 2. Inverse solution
13.3D Sorting and Grasping Coursenew
  • 1.AprilTag ID sorting
  • 2.MediaPipe Gesture-AprilTag ID sorting
  • 3.MediaPipe Gesture-AprilTag distance sorting
  • 4.Block color sorting
  • 5.Block different shape sorting
  • 6.Yolov11 garbage sorting
14.3D Tracking Coursenew
  • 1.AprilTag Tracking
  • 2.Color Block Tracking
  • 3.KCF Object Tracking
15.3D Voice Control for Sorting & Tracking Coursenew
  • 1.Voice Control AprilTag ID Sorting
  • 2.Voice Control Color Block Sorting
  • 3.Voice Control Yolov11 Garbage Recognition Sorting
  • 4.Voice Control AprilTag Tracking
  • 5.Voice Control Color Block Tracking
  • 6.Voice Control Object Tracking
16.AI Model Basicsnew
  • 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
17.AI Model Developmentnew
  • 1.Register a model service provider account
  • 2. Configure API-KEY
  • 3. Introduction to Dify
  • 4. Basic Dify Features
  • 5. Deploy the RAG knowledge base
  • 6. AI Large Model Development - chatbot
  • 7. RAG knowledge base + chatbot
  • 8. AI agent workflow
18.AI Model – Text Versionnew
  • 1. Semantic understand instruction following
  • 2. Multimodal visual understand
  • 3. Text Large Model + robotic arm control
  • 4. Multimodal Large Model+video understanding
  • 5. Multimodal Large Model+robotic arm gripping
  • 6. Multimodal Large Model+robotic arm tracking
  • 7. Multimodal Large Model+robotic arm sorting
  • 8. Multimodal Large Model+robotic arm handling
  • 9. Multimodal Large Model+Color Blocks Back In Place
  • 10. Multimodal Large Model + Intent Prediction + Robotic Arm Gripping
  • 11. Text Large Model + YOLOv11 + Intelligent Garbage Classification
19.AI Model – Voice Versionnew
  • 1. Semantic understand instruction following
  • 2. Multimodal visual understand
  • 3. Text Large Model + robotic arm control
  • 4. Multimodal Large Model+video understanding
  • 5. Multimodal Large Model+robotic arm gripping
  • 6. Multimodal Large Model+robotic arm tracking
  • 7. Multimodal Large Model+robotic arm sorting
  • 8. Multimodal Large Model+robotic arm handling
  • 9. Multimodal Large Model+Color Blocks Back In Place
  • 10. Multimodal Large Model + Intent Prediction + Robotic Arm Gripping
  • 11. Text Large Model + YOLOv11 + Intelligent Garbage Classification
20.AI Model – Fun Applicationsnew
  • 1.AI Butler-Intent Inference
  • 2.AI Encyclopedia-Arithmetic Master
  • 3.AI Encyclopedia-You asked I Pointed
  • 4.AI Encyclopedia-Nutritional Analysis
  • 5.AI Encyclopedia-Problem Solving Expert
  • 6.AI Encyclopedia-English Spelling
  • 7.AI Butler-Garbage Sorting
  • 8.AI Top Chef
21.MoveIt2 Course
  • 1.MoveIt configuration
  • 2. MoveIt Usage
  • 3. MoveIt Drive Real Robot
  • 4. MoveIt Random Movement
  • 5. MoveIt Forward Kinematics Design
  • 6. MoveIt Inverse Kinematics Design
  • 7. MoveIt Cartesian Path
  • 8. MoveIt Scene Design
  • 9. MoveIt Trajectory Planning
  • 10. MoveIt Collision Detection
22.YOLOv11 Development Course
  • 1. YOLO Environment Setup
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 6. Image Classification
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model Conversion
  • 9. Model Prediction
23.Linux Operating System
  • 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.Capacity expansion and resource allocation
  • 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
24.GPIO Hardware Control Course
  • 1.GPIO description
  • 2.GPIO library installation
  • 3.GPIO reading
  • 4.GPIO output
  • 5.Serial communication
  • 6.I2C communication
25.OpenCV course
  • 0. Must Read!
  • 1. Introduction to Open Source CV
  • 2. Image reading and display
  • 3. Image writing
  • 4. Image quality
  • 5. Pixel Operation
  • 6.Image zoom
  • 7.Picture cut
  • 8.Picture pan
  • 9.Picture mirroring
  • 10.Affine transformation
  • 11.Picture rotation
  • 12.perspective transformation
  • 13.Grayscale processing
  • 14.Binary image
  • 15.Edge green detection
  • 16.Line segment drawing
  • 17.Rectangular circle drawing
  • 18.Text and picture drawing
26.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
27. Advanced Visuals Course
  • 0. Must Read! Porting and Compilation
  • 1. QR Code
  • 2. Human Pose Estimation
  • 3. Object Detection
  • 4. AR Vision
  • 5. ROS + OpenCV Basics
28.Jupyter Lab Usage Course
  • 0.Read the document before operation
  • 1.Jupyter Lab environment construction
  • 2.Basic use of Jupyter Lab
  • 3.Jupyter Lab plug-in installation
  • 4.Basic use of Jupyter Widgets
29.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.Start the Dofbot container
30.Python Programming Basics
  • 1.Python usage
  • 2.Use APT to install Python packages
  • 3.Python virtual environment
  • 4.GPIO Zero
  • 5.Pin output high and low levels
  • 6.Pin reads high and low levels
  • 7.Pin output PWM
Download
  • APP(iOS/Android)
  • Code
  • SystemFile
  • VM File
  • PC software
  • Instruction manual
  • Jetson_Boot_USB.tar.gz
  • More Annex
  • Tools
Download ZIP
FAQ
  • 1、Precautions for DIY Robotic Arm
  • 2、Why i can't robotic arm start normally
  • 3、When you control the No.1 servo, all servos will turn.
  • 4、How open VNC service on DOFBOT system
  • 5、Where can I get the URDF file?
  • 6、Gesture recognition cannot work normally.
  • 7、Write system image into U disk
  • 8、Write EMMC boot file

Welcome to DOFBOT-JetsonNANO repository

1.Docker overview and docker installation

1、Docker overview and docker installation

At present, ROS2's courses are all placed in Docker containers, and customers can experience learning to use containerized development methods.

Raspberry Pi PI5Master Control’s ROS1 courses are all in docker containers.

1、Docker overview and docker installation1.1、Docker overview1.1.1、why docker appears1.1.2、Docker's core idea1.1.3、Compare virtual machines to Docker1.1.4、docker architecture1.1.5、Docker core objects1.1.6、images, containers, repositories1.1.7、Docker operation mechanism1.2、docker installation

Docker Chinese website: https://www.docker-cn.com

Docker Hub (repository) official website: https://hub.docker.com

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

1.1、Docker overview

Docker is an application container engine project, developed based on the Go language and open source.

 

1.1.1、why docker appears

Let's start with a few scenarios:

  1. O&M deploys the project you developed to the server, telling you that there is a problem and cannot be started. You ran around locally and found that there was no problem...

  2. The project to be launched is unavailable due to the update of some software versions...

  3. There are a lot of environmental content involved in the project, various middleware, various configurations, and the deployment of multiple servers...

These problems can actually be summed up in relation to the environment. To avoid various problems caused by different environments, it is best to deploy the project together with the various environments required by the project. For example, the project involves environments such as REDIS, MYSQL, JDK, ES, etc., and the entire environment is brought with you when deploying the JAR package. So the question is, how can you bring the project with the environment?

Docker is here to solve this problem!

1.1.2、Docker's core idea

 

image-20230424111123951

This is the logo of Docker, a whale full of containers, on the back of the whale, the containers are isolated from each other, which is the core idea of Docker. For example, if there were multiple applications running on the same server before, there may be port occupation conflicts of software, but now they can run alone after isolation. In addition, Docker can maximize the power of the server.

1.1.3、Compare virtual machines to Docker

 

  • The docker daemon can communicate directly with the main operating system to allocate resources to individual docker containers; It can also isolate containers from the main operating system and isolate individual containers from each other. Virtual machines take minutes to start, while docker containers can start in milliseconds. Since there is no bloated from the operating system, Docker can save a lot of disk space as well as other system resources.

  • Virtual machines are better at completely isolating the entire operating environment. For example, cloud service providers often use virtual machine technology to isolate different users. Docker is often used to isolate different applications, such as front-end, back-end, and database.

  • Docker containers are more resource-efficient and faster (start, shut down, create, delete) than virtual machines

1.1.4、docker architecture

Docker uses a client-server architecture. The Docker client communicates with the Docker daemon, which is responsible for building, running, and distributing the Docker container. The Docker client and daemon can run on the same system, or you can connect a Docker client to a remote Docker daemon. The docker client and daemon communicate using REST APIs over UNIX sockets or network interfaces. Another Docker client is Docker Compose, which lets you work with applications that consist of a set of containers.

30f24e4195234f58afbe43525dd57504

 

  • docker client is a docker command that is used directly after installing docker.

  • Docker host is our docker host (i.e. the operating system on which docker is installed)

  • Docker Daemon is Docker's background daemon that listens for and processes Docker client commands and manages Docker objects such as images, containers, networks, and volumes.

  • registry is a remote repository where docker pulls images, providing a large number of images for download, and saving them in images (local image repository) after downloading.

  • Images is a local image repository of docker, and image files can be viewed through docker images.

1.1.5、Docker core objects

 

1.1.6、images, containers, repositories

Image:

A docker image is a read-only template. Images can be used to create docker containers, and one image can create many containers. Just like classes and objects in Java, classes are images and containers are objects.

Container:

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Docker uses containers to run independently of an application or set of applications. A container is a running instance created from an image. It can be started, started, stopped, removed. Each container is an isolated platform for security. Think of a container as a simple version of the Linux environment (including root privileges, process space, user space, network space, etc.) and the applications running in it. The definition of a container is almost identical to an image, and it is also a unified view of a bunch of layers, the only difference is that the top layer of the container is readable and writable.

Repository:

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A repository is a place where image files are stored centrally. Repositories are divided into two forms: public repositories and private repositories.
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.

You need to correctly understand the concepts of warehousing/image/container:

  • Docker itself is a container runtime carrier, or management engine. We package the application and configuration dependencies to form a shippable runtime environment, and this packaged runtime environment is like an image image file. Only this image file can generate a docker container. An image file can be thought of as a template for a container. Docker generates an instance of the container from the image file. The same image file allows you to generate multiple container instances running at the same time.

  • The container instance generated by the image file is itself a file, called an image file.

  • A container runs a service, and when we need it, we can create a corresponding running instance through the docker client, which is our container.

  • As for the repository, it is a place where a bunch of images are placed, we can publish the images to the repository, and pull them from the repository when needed.

1.1.7、Docker operation mechanism

Docker pull execution process:

  1. The client sends instructions to Docker Daemon

  2. Docker Daemon first check whether there are relevant images in the local images

  3. If there is no relevant image locally, request the mirror server to download the remote mirror to the local computer

docker run execution process:

  1. Check whether the specified image exists locally and download it from the public repository

  2. Create and start a container from the image

  3. Assign a file system (lite Linux system) and mount a read-write layer outside the read-only image layer

  4. Bridge a virtual interface from the bridge interface configured by the host to the container

  5. Configure an IP address from the address pool to the container

  6. Execute the application specified by the user

1.2、docker installation

  1. Official website installation reference manual: https://docs.docker.com/engine/install/ubuntu/

  2. You can use the following commands to install with one click:

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curl -fsSL https://get.docker.com | bash -s docker --mirror Aliyun
  1. Check the docker version

xxxxxxxxxx
sudo docker version

image-20230424113920974

  1. Test the command

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sudo docker run hello-world

The following output indicates that the Docker installation was successful

image-20230424113848585

Basic use of Jupyter Widgets
Common commands for docker image containers

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