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DOFBOT-Pi📖
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
  • System Image
  • VM File
  • PC software
  • Instruction manual
  • More Annex
  • Tools
Download ZIP
FAQ
  • 1、Precautions for DIY Robotic Arm
  • 2、Where i can to check Raspberry Pi 4 Version tutorials?
  • 3、When you control the No.1 servo, all servos will turn.
  • 4、Dofbot start up process video
  • 5、Gesture recognition cannot work normally
  • 6、How to write image file into SD card
  • 7、How open VNC service on DOFBOT system
  • 8、Where can I get the URDF file?

Welcome to DOFBOT-Pi repository

1.MoveIt configuration

MoveIt2 Configuration

Not a required course: The provided system has already been configured.

MoveIt2 Configuration1. Environment Setup1.1. Install MoveIt21.2. Create Folder2. MoveIt2 Configuration2.1. Start Assistant2.2. Collision Detection2.3. Virtual Joints2.4. Motion Planning Groups2.5. Robot Poses2.6. End Effector2.7. Passive Joints2.8. URDF Files2.9. ROS2 Controllers2.10. MoveIt Controllers2.11. Sensors2.12. Launch Files2.13. Author Information2.14. Generate Configuration3. Configuration Files4. Configuration Verification4.1. Modify Configuration Files4.2. Compile Package4.3. Launch MoveItReferences

MoveIt2 is an advanced software framework for robot motion simulation, planning, and control.

1. Environment Setup

ROS2: Humble

If you are using a Jetson Nano development board, you will need to enter the commands from the tutorial into the accompanying virtual machine to run this function.

1.1. Install MoveIt2

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sudo apt install ros-humble-moveit*

Jetson Orin series boards have been tested and can directly run MoveIt2 related cases. The overall smoothness is acceptable!

1.2. Create Folder

The virtual machine has been created.

Create MoveIt2 auto-generated configuration files:

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mkdir ~/dofbot_pro_ws/src/dofbot_pro_moveit

2. MoveIt2 Configuration

MoveIt Setup Assistant is a graphical tool used to simplify and accelerate the creation and configuration of MoveIt2 configuration packages.

Through this tool, users can easily generate configuration files for robot motion planning and control without manually editing complex configuration files.

2.1. Start Assistant

Start MoveIt Setup Assistant:

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ros2 launch moveit_setup_assistant setup_assistant.launch.py

For first use, you can choose to create a new MoveIt configuration package. For later simple modifications, you can choose to edit an existing MoveIt package:

image-20250305174800376

Creating a new MoveIt configuration package requires importing the robot's URDF model: Simply importing the URDF model file to MoveIt Assistant will cause an error. You need to use the compiled package (dofbot_pro_description) URDF file path

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/home/yahboom/dofbot_ws/src/dofbot_urdf/urdf/dofbot.urdf

image-20250305175943869

After selecting the URDF file, click Load Files, and MoveIt Assistant will display the robot model:

image-20260317114620726

2.2. Collision Detection

The self-collision matrix is a feature used to optimize motion planning. Its main purpose is to generate a matrix that describes whether various links in the robot model may collide with each other.

This matrix can help the motion planner avoid unnecessary collision detection during path planning, thereby improving planning efficiency.

To generate the self-collision matrix, you can click the auto-generate option in MoveIt Setup Assistant:

image-20260317114708609

image-20260317114730720

2.3. Virtual Joints

Virtual joints are used to define the relationship between the robot model and the external world.

Virtual joints are typically used to describe the connection between the robot base and a fixed reference frame (such as the world coordinate system).

image-20260317115048403

Fix the robot base link base_link and world:

  • Virtual Joint Name: virtual_joint
  • Child Link: base_link
  • Parent Frame Name: world
  • Joint Type: fixed

image-20260317115140129

image-20260317115206678

2.4. Motion Planning Groups

Planning groups are key steps in configuring robot motion planning.

Planning groups define which joints and links in the robot can move together and how their motion is planned.

image-20260317115238063

Plan robotic arm group: arm_group

  • Group Name:arm_group
  • Kinematic Solver:kdl_kinematics_plugin/KDLKinematicsPlugin
  • Kin. Search Resolution:0.005
  • Kin. Search Timeout:0.005

image-20260317115326951

  • Add Joints:Select the robotic arm joints

Joints:Arm1_Joint、Arm2_Joint、Arm3_Joint、Arm4_Joint、Arm5_Joint

image-20260317115424990

image-20260317115520862

Plan Gripper Group:grip_group

image-20260317115604416

 

Plan gripper group: grip_group

  • Group Name:grip_group
  • Kinematic Solver:None
  • Kin. Search Resolution:0.005
  • Kin. Search Timeout:0.005

image-20260317115849145

  • Add Links:Select the gripper links

Links:rlink1、rlink2、rlink3

image-20260317122529131

2.5. Robot Poses

Robotic Arm Positions

Set three groups of robotic arm predefined poses to the robot configuration:

image-20260317120348634

You can manually move the sliders to set each joint state: up、down、init

image-20260317120444868

image-20260317120707779

image-20260317121122168

Gripper Positions

Set two groups of gripper predefined poses to the robot configuration:

image-20250305192100132

You can manually move the sliders to set gripper state: open、close

image-20260317142924688

image-20260317143320699

2.6. End Effector

Set the gripper group as the end effector:

image-20260317143411687

End effector: gripper

  • End Effector Name:gripper
  • End Effector Group:gripp_group
  • Parent Link:Arm5_Link
  • Parent Group:None

image-20260317143502690

image-20260317143529101

2.7. Passive Joints

Passive joints are non-driven joints that cannot be directly controlled: The robotic arm has no passive joints, so skip this step.

image-20260317143612978

2.8. URDF Files

MoveIt Setup Assistant will automatically set command interfaces and state interfaces for each joint: Use the default generated information.

image-20260317143634829

2.9. ROS2 Controllers

ROS2 Controllers is a framework for robot real-time control, which can be used to automatically generate simulation controllers to drive robot joints.

image-20260317143705795

Add robotic arm controller:

  • Controller Name:arm_group_controller
  • Controller Type:joint_trajectory_controller/JointTrajectoryController
  • Add Planning Group Joints:arm_group

image-20260317143840120

image-20260317143856265

Add gripper controller:

  • Controller Name:grip_group_controller
  • Controller Type:position_controllers/GripperActionController
  • Add Planning Group Joints:grip_group

image-20260317143919517

image-20260317144012949

image-20260317144047777

image-20260317144235181

2.10. MoveIt Controllers

MoveIt requires trajectory controllers with the FollowJointTrajectoryAction interface to execute planned trajectories. This interface sends the generated trajectories to the robot's ROS2 controllers.

The added MoveIt Controllers need to ensure that the controller names match the names configured in ROS2 Controllers.

image-20260317144321443

Add robotic arm controller:

  • Controller Name:arm_group_controller
  • Controller Type:FollowJointTrajectory
  • Add Planning Group Joints:arm_group

image-20260317144402993

image-20260317144433432

image-20260317144447412

Add gripper controller:

  • Controller Name:grip_group_controller
  • Controller Type:Gripper Command
  • Add Planning Group Joints:grip_group

image-20260317144505929

image-20260317144545319

image-20260317144621987

image-20260317144641893

2.11. Sensors

Configure the settings for 3D sensors used by the robot: No configuration needed.

image-20260317144657623

2.12. Launch Files

Configure auto-generated launch files: Use default options.

image-20260317144711163

2.13. Author Information

Add author information for package generation:

image-20260317144734515

2.14. Generate Configuration

Generate configuration files to the specified folder:

image-20260317144836547

Then click Generate Package. image-20250305194502418

image-20250305194516124

3. Configuration Files

Enter the dofbot_moveit folder:

image-20260317145007834

4. Configuration Verification

The configuration files generated by MoveIt Setup Assistant need simple modifications to remove startup warnings and model loading issues.

4.1. Modify Configuration Files

dofbot_urdf.ros2_control.xacro

Modify the dofbot_urdf.ros2_control.xacro file: Modify the yaml loading function

image-20260317150259036

joint_limits.yaml

image-20260317145159604

4.2. Compile Package

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cd ~/dofbot_ws
colcon build --packages-select dofbot_moveit
source install/setup.bash

4.3. Launch MoveIt

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ros2 launch dofbot_pro_moveit demo.launch.py

The simulation startup is relatively slow. Wait until the terminal shows You can start planning now! or the robotic arm shows trajectory balls (trajectory balls are new spheres added to the robotic arm), indicating loading is complete.

image-20260317150202330

References

MoveIt2 Humble:https://moveit.picknik.ai/humble/index.html

MoveIt2:https://moveit.picknik.ai/main/index.html

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