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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

1. Dabai_DCW2 camera

Dabai_DCW2 Camera

Please ensure that the web control program backend process is not running in the background. To close it, refer to the [Get Started Quickly - 2. Access the Terminal] section in [Disable the Auto-Start Web Control Backend Process]. After closing, please restart DofbotUltra!!!

Before starting this function, you need to close the web control program backend process.

1. Function Description

After starting the camera, you can obtain RGB color images, Depth images, and IR infrared images.

2. Startup and Operation

2.1 Startup

After connecting the camera to the motherboard via data cable, open the terminal and enter:

xxxxxxxxxx
ros2 launch orbbec_camera dabai_dcw2.launch.py

As shown in the figure below, when the terminal prints the above content, it means the camera is running normally and startup is successful. You can view the topics published by the camera node using the following command:

image-20250415094737199

xxxxxxxxxx
ros2 node info /camera/camera

As shown in the figure below, the published color image topic is /camera/color/image_raw, the published depth image topic is /camera/depth/image_raw, the published infrared image topic is /camera/ir/image_raw, and the published point cloud data topic is /camera/depth/points.

image-20250415094930453

2.2 Operation

Use rviz to view the camera's three images and point cloud. Open a new terminal and enter:

xxxxxxxxxx
rviz2

After rviz starts, configure rviz according to the instructions in the figures below:

image-20240923151317605

Change the Fixed Frame to camera_link.

Add Color Image Display

image-20240923151723919

Click Add, then click By topic, select /color/image_raw/Image, and finally click OK to confirm. The color image will be displayed as follows:

image-20240923151949732

Add Depth Image Display

image-20240923152144334

Click Add, then click By topic, select /depth/image_raw/Image, and finally click OK to confirm. The depth image will be displayed as follows:

image-20240923152242374

Add Infrared Image Display

image-20240923152423870

Click Add, then click By topic, select /ir/image_raw/Image, and finally click OK to confirm. The infrared image will be displayed as follows:

image-20240923152507428

View Depth Point Cloud Data

image-20240923152817924

Click Add, then click By topic, select /depth/points/PointCloud2, and finally click OK to confirm. The depth point cloud image will be displayed as follows:

If you cannot see the point cloud, please check if Fixed Frame is set to camera_link.

image-20240923152956800

View Colored Point Cloud Data

image-20250415102030489

Click Add, then click By topic, select /depth_registered/points/PointCloud2, and finally click OK to confirm. The colored point cloud image will be displayed as follows:

image-20240923153713210

3. Camera Parameters

3.1 Hardware Parameters

image-20240923154415732

3.2 Camera Parameter Retrieval and Settings

The camera's initialization parameters are already set in the launch file that was started. The launch file path is:

xxxxxxxxxx
Raspberry Pi: /home/yahboom/dofbot_ultra_ws/src/OrbbecSDK_ROS2/orbbec_camera/launch/dabai_dcw2.launch.py
RDK: /home/sunrise/dofbot_ultra_ws/src/OrbbecSDK_ROS2/orbbec_camera/launch/dabai_dcw2.launch.py

The contents are as follows:

xxxxxxxxxx
from launch import LaunchDescription
from launch.actions import DeclareLaunchArgument
from launch.substitutions import LaunchConfiguration
from launch_ros.actions import PushRosNamespace
from launch.actions import GroupAction
from launch_ros.actions import ComposableNodeContainer
from launch_ros.descriptions import ComposableNode
from launch_ros.actions import Node
import os


def generate_launch_description():
    # Declare arguments
    args = [
        DeclareLaunchArgument('camera_name', default_value='camera'),
        DeclareLaunchArgument('depth_registration', default_value='true'),
        DeclareLaunchArgument('serial_number', default_value=''),
        DeclareLaunchArgument('usb_port', default_value=''),
        DeclareLaunchArgument('device_num', default_value='1'),
        DeclareLaunchArgument('vendor_id', default_value='0x2bc5'),
        DeclareLaunchArgument('product_id', default_value=''),
        DeclareLaunchArgument('enable_point_cloud', default_value='true'),
        DeclareLaunchArgument('enable_colored_point_cloud', default_value='true'),
        DeclareLaunchArgument('cloud_frame_id', default_value=''),
        DeclareLaunchArgument('point_cloud_qos', default_value='default'),
        DeclareLaunchArgument('connection_delay', default_value='100'),
        DeclareLaunchArgument('color_width', default_value='640'),
        DeclareLaunchArgument('color_height', default_value='480'),
        DeclareLaunchArgument('color_fps', default_value='30'),
        DeclareLaunchArgument('color_format', default_value='MJPG'),
        DeclareLaunchArgument('enable_color', default_value='true'),
        DeclareLaunchArgument('flip_color', default_value='false'),
        DeclareLaunchArgument('color_qos', default_value='default'),
        DeclareLaunchArgument('color_camera_info_qos', default_value='default'),
        DeclareLaunchArgument('enable_color_auto_exposure', default_value='true'),
        DeclareLaunchArgument('color_exposure', default_value='-1'),
        DeclareLaunchArgument('color_gain', default_value='-1'),
        DeclareLaunchArgument('enable_color_auto_white_balance', default_value='true'),
        DeclareLaunchArgument('color_white_balance', default_value='-1'),
        DeclareLaunchArgument('color_ae_max_exposure', default_value='-1'),
        DeclareLaunchArgument('color_brightness', default_value='-1'),
        DeclareLaunchArgument('color_sharpness', default_value='-1'),
        DeclareLaunchArgument('color_saturation', default_value='-1'),
        DeclareLaunchArgument('color_contrast', default_value='-1'),
        DeclareLaunchArgument('color_gamma', default_value='-1'),
        DeclareLaunchArgument('color_hue', default_value='-1'),
        DeclareLaunchArgument('depth_width', default_value='640'),
        DeclareLaunchArgument('depth_height', default_value='400'),
        DeclareLaunchArgument('depth_fps', default_value='15'),
        DeclareLaunchArgument('depth_format', default_value='Y11'),
        DeclareLaunchArgument('enable_depth', default_value='true'),
        DeclareLaunchArgument('flip_depth', default_value='false'),
        DeclareLaunchArgument('depth_qos', default_value='default'),
        DeclareLaunchArgument('depth_camera_info_qos', default_value='default'),
        # /config/depthfilter/Openni_device.json, need config path.
        DeclareLaunchArgument('depth_filter_config', default_value=''),
        DeclareLaunchArgument('ir_width', default_value='640'),
        DeclareLaunchArgument('ir_height', default_value='400'),
        DeclareLaunchArgument('ir_fps', default_value='15'),
        DeclareLaunchArgument('ir_format', default_value='Y10'),
        DeclareLaunchArgument('enable_ir', default_value='true'),
        DeclareLaunchArgument('flip_ir', default_value='false'),
        DeclareLaunchArgument('ir_qos', default_value='default'),
        DeclareLaunchArgument('ir_camera_info_qos', default_value='default'),
        DeclareLaunchArgument('enable_ir_auto_exposure', default_value='true'),
        DeclareLaunchArgument('ir_exposure', default_value='-1'),
        DeclareLaunchArgument('ir_gain', default_value='-1'),
        DeclareLaunchArgument('publish_tf', default_value='true'),
        DeclareLaunchArgument('tf_publish_rate', default_value='0.0'),
        DeclareLaunchArgument('ir_info_url', default_value=''),
        DeclareLaunchArgument('color_info_url', default_value=''),
        DeclareLaunchArgument('log_level', default_value='none'),
        DeclareLaunchArgument('enable_publish_extrinsic', default_value='false'),
        DeclareLaunchArgument('enable_soft_filter', default_value='true'),
        DeclareLaunchArgument('enable_ldp', default_value='true'),
        DeclareLaunchArgument('soft_filter_max_diff', default_value='-1'),
        DeclareLaunchArgument('soft_filter_speckle_size', default_value='-1'),
        DeclareLaunchArgument('ordered_pc', default_value='false'),
        DeclareLaunchArgument('use_hardware_time', default_value='false'),
        DeclareLaunchArgument('enable_depth_scale', default_value='true'),
        DeclareLaunchArgument('align_mode', default_value='HW'),
        DeclareLaunchArgument('laser_energy_level', default_value='-1'),
        DeclareLaunchArgument('enable_heartbeat', default_value='false'),
    ]

    # Node configuration
    parameters = [{arg.name: LaunchConfiguration(arg.name)} for arg in args]
    # get  ROS_DISTRO
    ros_distro = os.environ["ROS_DISTRO"]
    if ros_distro == "foxy":
        return LaunchDescription(
            args
            + [
                Node(
                    package="orbbec_camera",
                    executable="orbbec_camera_node",
                    name="ob_camera_node",
                    namespace=LaunchConfiguration("camera_name"),
                    parameters=parameters,
                    output="screen",
                )
            ]
        )
    # Define the ComposableNode
    else:
        # Define the ComposableNode
        compose_node = ComposableNode(
            package="orbbec_camera",
            plugin="orbbec_camera::OBCameraNodeDriver",
            name=LaunchConfiguration("camera_name"),
            namespace="",
            parameters=parameters,
        )
        # Define the ComposableNodeContainer
        container = ComposableNodeContainer(
            name="camera_container",
            namespace="",
            package="rclcpp_components",
            executable="component_container",
            composable_node_descriptions=[
                compose_node,
            ],
            output="screen",
        )
        # Launch description
        ld = LaunchDescription(
            args
            + [
                GroupAction(
                    [PushRosNamespace(LaunchConfiguration("camera_name")), container]
                )
            ]
        )
        return ld

After the camera is running, we can use some services to retrieve or set certain parameters. For example, to get the exposure value and set the exposure value, first query what services the camera node can call. Enter in the terminal:

xxxxxxxxxx
ros2 node info /camera/camera

As shown in the figure below, after the camera node starts, it provides the following services:

image-20250415100304367

3.2.1 Camera Parameter Retrieval

Taking getting the exposure value as an example, call the service and enter in the terminal:

xxxxxxxxxx
ros2 service call /camera/get_color_exposure orbbec_camera_msgs/srv/GetInt32 '{}'

As shown in the figure below, the obtained exposure value is 100.

image-20250415101115535

3.2.2 Camera Parameter Setting

Taking the auto exposure value switch as an example, call the service and enter in the terminal:

xxxxxxxxxx
ros2 service call /camera/set_color_auto_exposure std_srvs/srv/SetBool '{data: true}'

image-20250415101613528

Manual setting:

xxxxxxxxxx
ros2 service call /camera/set_color_exposure orbbec_camera_msgs/srv/SetInt32 '{data: 50}'

image-20250415182707647

After setting the auto exposure value, the color image will change the exposure value according to the environment settings.

image-20240923153713210

Garbage Sorting with Voice Broadcast
Deep pseudo-color image

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