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DOFBOT-Ultra📖
1. Get Started Quickly
  • 0.Unboxing Video
  • 1. Get Started Quickly
  • 2. Access the Terminal
  • 3. Calibration offset(Depth Camera)
  • 4. Calibration offset(USB Camera)
2. Assembly Course
  • 1. Installation Steps
  • 2. Calibrate the Robotic Arm
  • 3. Install the Map
3. Remote Control Course
  • 1. Mobile Phone Control
  • 2. USB Handle Control
  • 3. PC Web Page Programming
4. Preparation
  • 1. Manage Web control services
  • 2. Manage JupyterLab services
  • 3. Manage OLED services
5. 2D Visual Tracking Course
  • 1. Color block positioning
  • 2. Color block tracking
  • 3. Face positioning
  • 4. Face tracking
  • 5. Label code positioning
  • 6. Label code tracking
6. 2D Visual Grasping Course
  • 1. Identify grab color block
  • 2. Catch game
  • 3. Color sorting
  • 4. Color stacking
  • 5. Label code sorting
  • 6. Label code stacking
  • 7. Gesture grasping color blocks
  • 8. Gesture stacking color blocks
  • 9. Single garbage sorting
  • 10. Garbage sorting
  • 11. Tracking game
7. 2D Mediapipe Course
  • 1. Hand detection
  • 2. 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
8. AI Large Model Voice Module (Must Read)
  • 1. Introduction to AI Large Model Voice Module
  • 2. Flash the firmware (Must read)
  • 3. Modify the wake-up word and command word
9. 2D Voice Control Course
  • 1. Simple Voice Control
  • 2. Smart Voice Control
  • 3. Voice Action Control
  • 4. Memory Learning Mode
  • 5. Color Recognition with Voice Broadcast
  • 6. Color Recognition and Grasping with Voice Broadcast
  • 7. Color Recognition and Sorting with Voice Broadcast
  • 8. Voice Recognition Target Tracking
  • 9. Voice Control Stacking
  • 10. Voice Control Sorting
  • 11. Garbage Recognition with Voice Broadcast
  • 12. Garbage Sorting with Voice Broadcast
10. 3D Depth Camera Course
  • 1. Dabai_DCW2 camera
  • 2. Deep pseudo-color image
  • 3. Depth camera ranging
  • 4. Color block volume measurement
11. 3D Robotic Arm Control and Inverse Kinematics
  • 1. Robotic arm ROS control
  • 2. Inverse solution
12. 3D Sorting and Grasping Course
  • 1. AprilTag ID sorting
  • 2. AprilTag abnormal height sorting
  • 3. MediaPipe Gesture-AprilTag ID sorting
  • 4. MediaPipe Gesture-AprilTag height sorting
  • 5. MediaPipe Gesture-AprilTag distance sorting
  • 6. Block color sorting
  • 7. Block abnormal height sorting
  • 8. Block different shape sorting
  • 9. Block shape abnormal height sorting
  • 10. Yolov26 garbage sorting
13. 3D Tracking and Grasping Course
  • 1. AprilTag Tracking and Grasping
  • 2. Color Block Tracking and Grasping
  • 3. KCF Object Tracking and Grasping
14. 3D Voice Control for Grasping Course (Sorting & Tracking)
  • 1. Voice Control AprilTag ID Sorting
  • 2. Voice Control Remove Height Abnormal AprilTag
  • 3. Voice Control Tracking and Grasping AprilTag
  • 4. Voice Control Color Block Sorting
  • 5. Voice Control Remove Height Abnormal Color Block
  • 6. Voice Control Tracking and Grasping Color Block
  • 7. Voice Control Yolov26 Garbage Recognition Sorting
  • 8. Voice Control Object Tracking and Grasping
15. 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
16. AI Model Development
  • 0. DofbotUltra Large Model Development Quick Start Guide
  • 1. Register a Model Service Provider Account
  • 2. Configure API-KEY
  • 3. Introduction to Dify
  • 4. Basic Dify Features
  • 5. AI Large Model Development - chatbot
  • 6. Deploy the RAG knowledge base
  • 7. RAG knowledge base + chatbot
  • 8. AI agent workflow
17. AI Model – Text Version
  • 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 + YOLOv26 + Intelligent Garbage Classification
18. AI Model – Voice Version
  • 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 + YOLOv26 + Intelligent Garbage Classification
19. AI Model – Fun Applications
  • 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
20. MoveIt 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
21. YOLOv11 Development Course
PI 5
  • 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. Dataset Annotation
  • 10. Model Training and Conversion
  • 11. Model Prediction
RDK X5
  • 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 Prediction
  • 9. Model Conversion
22. YOLOv26 Development Course
PI 5
  • 6. Image Classification
  • 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. Dataset Annotation
  • 10. Model Training and Conversion
  • 11. Model Prediction
RDK X5
  • 1. YOLO Environment Setup
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model Conversion
  • 9. Dataset Annotation
  • 10. Model Training and Conversion
  • 11. 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. Basic Control Course
  • 1. Control RGB Light
  • 2. Control Buzzer
  • 3. Control Single Servo
  • 4. Read Servo Angle
  • 5. Control All Servos
  • 6. DOFBOT Up Down Left Right Movement
  • 7. DOFBOT Dancing
  • 8. DOFBOT Memory Actions
  • 9. DOFBOT Grab Blocks
  • 10. Porter
  • 11. Stack Blocks
  • 12. Two DOFBOT Synchronized Actions
25.RDKx5 Board Basic Course
  • 1.Introduction to RDK X5 board
  • 2.Write system file
  • 3.Hardware interface description
  • 4.Install case and other accessories
  • 5.Use 7-inch display
  • 6.SD card expansion
  • 7.Network configuration
  • 8.Remote login
  • 9.Update system
  • 10.srpi-config user guide
  • 11.config. txt configuration file
  • 12.Self-startup setting
  • 13.RDK exclusive command usage
  • 14.Linux command usage
  • 15.GPIO readwrite operation
  • 16.Image classification algorithm
  • 17.Use USB camera
  • 18.Use MIPI camera
  • 19.Binocular camera depth algorithm
26.PI5 Board Basic Course
  • 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.Installation and introduction of shell and active radiator
  • 6.GPIO and 40-pin pins
  • 7.Tips for using Raspberry PI 5
  • 8.Raspberry PI PCIe connector
  • 9.MIPI CSI DSI connector
  • 10.UART connector
  • 11.Real-time clock
  • 12.Power over Ethernet (PoE) connector
  • 13.Update and upgrade operating system
  • 14.Introduction to raspi-config tool
  • 15.config.txt file description
  • 16.Network Configuration
  • 17.remote access
  • 18.Transfer files remotely
  • 19.Set display resolution and rotation
  • 20.Set screen to sleep
  • 21.Get real-time temperature of Raspberry Pi
  • 22.Play audio and video
  • 23.Using USB camera
  • 24.Using MIPI camera
27. Visual 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. 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 Detection
  • 16. Line Segment Drawing
  • 17. Rectangular Circle Drawing
  • 18. Text and Picture Drawing
28. 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
29. Jupyter Lab Usage Course
  • 1. Read the document before operation
  • 2. Jupyter lab environment construction tutorial
  • 3. Basic tutorial of Jupyter lab
  • 4. Jupyter widgets configuration tutorial
  • 5. Getting Started Tutorial for JupyterWidgets Controls
Download
  • System_File
  • VM_File
  • Instruction Manual
  • Code
  • Software Tools
  • Communication_Protocols
  • Hardware_Info
Download ZIP

Welcome to DOFBOT-Ultra repository

17.ROS2 rviz2 use

17. Using ROS2 Rviz2

1. Introduction to Rviz2

During robot development, various functions require analysis at the data level, making it difficult to quickly understand their impact. For example, for robot models, we need to understand the design's appearance and the positions of the model's numerous internal coordinate systems during motion.

For robotic arm motion planning and mobile robot autonomous navigation, we need to visualize the robot's surrounding environment, the planned path, and, of course, sensor information, such as cameras, 3D cameras, and lidar. Data is used for calculations, while visualization is for human viewing.

Therefore, data visualization can greatly improve development efficiency. Rviz2 is such a data visualization software for robot development. It can handle everything from robot models, sensor information, and environmental information.

2. Preparation

  • If you have a physical robot, you can launch Rviz on the robot controller to practice this lesson. If you don't have a physical robot, you can use Gazebo to simulate a TurtleBot3 robot to simulate the lidar, camera, and other components, facilitating subsequent data visualization.

Note: The following installation steps are optional. If you have a physical robot and have set up multi-machine communication, you can directly use the actual robot's radar information. You can choose to use the actual radar or a simulated robot. The following information is for users without a physical robot.

  • This lesson uses a simulated robot as an example to teach you the visualization capabilities of Rviz2. The operation process is the same for both real and simulated robots.
  • Install the TutleBot3 simulator package
xxxxxxxxxx
sudo apt install ros-${ROS_DISTRO}-turtlebot3*
  • Install the ROS and Gazebo bridge tool
xxxxxxxxxx
sudo apt install ros-${ROS_DISTRO}-ros-gz
  • Set the TurtleBot3 robot type environment variable
xxxxxxxxxx
export TURTLEBOT3_MODEL=waffle
  • Start the Gazebo simulation environment
xxxxxxxxxx
ros2 launch turtlebot3_gazebo turtlebot3_world.launch.py

image-20250905164250419

3. Starting Rviz2

Open a terminal and run the following command to start it:

xxxxxxxxxx
rviz2

If starting in Docker, make sure the GUI is enabled.

image-20231031104047357

4. Image Data Visualization

Click "Add" in the Displays window on the left, find the Image display item, and confirm it to add it to the display list. Then, configure the image topic to which the display item is subscribed. You can then view the robot's camera image.

image-20231031104244974

  • Select Fixed Frame as the base_footprint coordinate system, and place the coordinate transformation error.
  • Select the camera color image topic /camera/image_raw.
  • Now you can see the current simulated robot's view in the Camera window.

image-20250905165626951

5. Radar Data Visualization

Click "Add" in the Displays window on the left, select Laserscan, and then configure the subscription topic name. You should now see the laser dot.

image-20231031104528033

  • Select /sacn in the LaserScan topic.
  • Now you can see the LiDAR point cloud outline.

image-20250905170346004

6. Robot Model Visualization

Click "Add" in the Displays window on the left and select RobotModel.

image-20250905170711426

  • In the robot's DescriptionTopic, select /robot_deseription.
  • Now you can see the robot model visualized in Rviz2.

image-20250905170923074

7. Other Data Visualizations

The rivz_default_plugins section lists many commonly used data visualization plugins. Feel free to try them out.

image-20231031104758824

ROS2 common command tools
ROS2 rqt toolbox

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