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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

4. Calibration offset(USB Camera)

Calibration Offset (Non-Depth Camera Version)

This tutorial is for standard USB 2D camera scenarios. Unlike the depth camera version, the non-depth camera calibration enters the Pixel-World Calibration script, which requires 6 fixed-point samples to generate the grasping mapping relationship.

Calibration Offset (Non-Depth Camera Version)Scope of Application2. Preparation Before Calibration3. Start the Calibration Wizard4. Calibration Interface Key Instructions5. 6-Point Guided Sampling StepsPoint 1: Mark CenterPoint 2: Far CenterPoint 3: Far + Left Side of FramePoint 4: Far + Right Side of FramePoint 5: Mark + Left Side of FramePoint 6: Mark + Right Side of Frame6. Calculation, Saving, and Online Verification7. Result File and Path Description8. Common Issues and Solutions9. Grasp Test

Scope of Application

  1. Applicable camera: Standard USB camera (not the DABAI_DCW2 depth camera).

    Check whether CAMERA_TYPE in ~/.bashrc is set to any value other than DABAI_DCW2.

  2. Calibration goal: Establish the mapping relationship between image pixel points and the robotic arm working plane coordinates (X/Y).

  3. Calibration method: Use the AprilTag to sample at 6 guided positions on the calibration board. The program automatically calculates the homography matrix.

  4. Calibration result: Saved to pixel_world_homography.npy for subsequent recognition and grasping processes.

image-20260408173811189

2. Preparation Before Calibration

  1. Ensure the robotic arm and USB camera are properly connected and the camera image can be read normally.
  2. Place the DOFBOT calibration board (30 cm x 21 cm) and the AprilTag (3 cm x 3 cm x 3 cm block) on the table.
  3. Ensure uniform ambient lighting, avoiding strong reflections and shadows that block the Tag.
  4. Fix the robotic arm body (place it in the designated area on the calibration board) during calibration. Only move the AprilTag position during sampling.
  5. Confirm that the current environment variable is not in depth camera mode: CAMERA_TYPE should not be DABAI_DCW2.

Recommended check command:

echo $CAMERA_TYPE

If the output is DABAI_DCW2, switch to standard USB mode and reload the environment.

image-20260408173906515

3. Start the Calibration Wizard

Run the following command in the terminal:

xxxxxxxxxx
ros2 run dofbot_ultra_driver calibration_wizard

The main menu will display the camera type and function items. In non-depth camera mode, option 1 is:

  1. Pixel-World Calibration (Board-Guided)
  2. Mechanical Bias & Height Comp Tuning
  3. Run Grasp Test Q. Quit

First select 1 to enter the guided 6-point calibration.

image-20260408173947199

4. Calibration Interface Key Instructions

Tip: When calibrating positions other than the first point, cover the fixed AprilTag on the calibration board to avoid interference.

Process summary: 1. Place the AprilTag at the specified position --> 2. Press SPACEBAR to sample --> 3. Repeat steps 1 and 2 six times for six points --> 4. Press the "C" key to complete calibration --> 5. Press Q to exit.

After entering the calibration window, the key logic is as follows:

  1. SPACEBAR: Sample the current point.
  2. S: Skip the current point (generally not used unless the point is truly uncollectable).
  3. C: Calculate and save the calibration result (at least 4 valid points are required; it is recommended to follow the guide and collect all six points).
  4. ESC: Exit the calibration process.

Notes:

  1. Each time the SPACEBAR is pressed, the program does not take a single-frame sample immediately. Instead, it performs a brief multi-frame sampling and averages the result to reduce jitter error.
  2. It is recommended to collect all 6 points, as accuracy is typically higher than with only 4 points.

Sample point illustration:

image-20260408174931111

5. 6-Point Guided Sampling Steps

The program will prompt 6 points in a fixed order. Follow the prompts to move the AprilTag center and align it with the corresponding edges.

Point 1: Mark Center

  1. Align the AprilTag center with the calibration board mark (X=18.1 cm, Y=0).
  2. Once stable, press the SPACEBAR to sample.

Point 2: Far Center

  1. Move the Tag to the far edge center (the side away from the arm).
  2. Press the SPACEBAR to sample.

Point 3: Far + Left Side of Frame

  1. Move the Tag to the intersection of the far edge and the left side of the frame (close to both edges).
  2. Press the SPACEBAR to sample.

Point 4: Far + Right Side of Frame

  1. Move the Tag to the intersection of the far edge and the right side of the frame (close to both edges).
  2. Press the SPACEBAR to sample.

Point 5: Mark + Left Side of Frame

  1. Return to the mark line height and move close to the left edge of the frame.
  2. Press the SPACEBAR to sample.

Point 6: Mark + Right Side of Frame

  1. Return to the mark line height and move close to the right edge of the frame.
  2. Press the SPACEBAR to sample.

Tips:

  1. After each successful sample, the interface will display the completed status.
  2. If the Tag is not recognized in the current frame, pressing the SPACEBAR will show a failure prompt. Adjust and retry.

image-20260408174654574

6. Calculation, Saving, and Online Verification

  1. After sampling, press C. The program will calculate the pixel-to-world coordinate transformation matrix.
  2. The terminal will output the error for each point, the average error, and the maximum error.
  3. After saving, enter online verification mode. Move the Tag to observe the real-time calculated world coordinates.
  4. Press ESC or Q to exit verification and return to the process end screen.

image-20260408175335868

7. Result File and Path Description

  1. Calibration result file name: pixel_world_homography.npy.
  2. The save directory is the driver configuration path (the program automatically selects a valid directory).

Raspberry Pi configuration directory:

xxxxxxxxxx
/home/yahboom/dofbot_ultra/core/dofbot_ultra_driver/config

RDK X5 configuration directory:

xxxxxxxxxx
/home/sunrise/dofbot_ultra_ws/src/core/dofbot_ultra_driver/config

8. Common Issues and Solutions

  1. Black screen or camera not opening after entering calibration

    • Check if the camera is occupied by another process.
    • Re-run the calibration wizard and ensure standard USB mode is used.
  2. AprilTag not recognized

    • Adjust lighting and focus.
    • Ensure the Tag is clear, complete, and unobstructed.
  3. Large error and obvious grasping offset

    • Re-run the full 6-point sampling.
    • Ensure each point is aligned with the indicated edge position.
    • Avoid moving the arm or camera during sampling.
  4. Fixed deviation remains after calibration

    • Select option 2 (Mechanical Bias & Height Comp Tuning) from the main menu to fine-tune the mechanical error.

9. Grasp Test

After calibration is complete, you can immediately run a grasp test to verify the calibration result.

From the menu, select option 3 to enter the grasp test mode.

image-20260409095206864

After the block is recognized, press the SPACEBAR to grasp. The target position is the center-lower part of the block. Test grasping with the block at several different positions:

  1. If the grasp is accurate, calibration is successful.
  2. If there is a fixed deviation (always offset forward or backward), use option 2 (Mechanical Bias) from the menu to fine-tune the mechanical error.
  3. If the deviation is not fixed, recalibrate (minor deviations can be ignored).
Calibration offset(Depth Camera)
Installation Steps

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