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ROSMASTER X3 Plus📖
1.Preparation and First Trial
  • 1.1 Wiring Introduction
  • 1.2 Precautions for battery
  • 1.3 First Trial
  • 1.4 Precautions for DIY Robotic Arm
2. Assembly steps
  • Installation Video
3.Remote control course
  • 3.1 APP remote control
  • 3.2 Model aircraft remote control
  • 3.3 Handle remote control
4.Hardware course
  • 4.1 About expansion board_V3.0
  • 4.1 About expansion board_V1.0
  • 4.2 STM32 Development
  • 4.3 Button to control the buzzer
  • 4.4 FreeRTOS application
  • 4.5 Serial communication
  • 4.6 SBUS model aircraft remote control
  • 4.7 CAN bus communication
  • 4.8 RGB colorful light bar
  • 4.9 Timer interrupt to control
  • 4.10 Control serial port servos
  • 4.11 Nine-axis attitude sensor
  • 4.12 Control motor
  • 4.13 Timer captures the encoder data
  • 4.14 Kinematic Analysis
  • 4.15 PID control robot movement
5.Basic course
  • 5.1 Update the firmware
  • 5.2 Turn off the self-starting process
  • 5.3 Install the Rosmaster driver
  • 5.4 Buzzer whistle
  • 5.5 Control PWM servo
  • 5.6 RGB colorful light bar
  • 5.7 Control motor
  • 5.8 Control robot movement
  • 5.9 Control Serial Servo
6.Linux operating system
  • 6.1 Virtual machine installation
  • 6.2 Linux basics
  • 6.3 Remote control
  • 6.4 Multi-machine communication
  • 6.5 Static IP and hotspot mode
  • 6.6 Bind the device ID
  • 6.7 Web page real-time monitor
  • 6.8 Expansion tutorial
  • 6.9.1 Jetson Nano write sytem
  • 6.9.2 Jetson Xavier NX write system
  • 6.9.3 Jetson TX2 NX write system
  • 6.9.4 Raspberry Pi write system
7.Docker-Just for pi5
  • 7.1 Docker overview and docker installation
  • 7.2 Common commands for docker image containers
  • 7.3 Docker images deeply understand and publish images
  • 7.4 Docker hardware interaction and data processing
  • 7.5 Enter the bot's docker container
  • 7.6 Robot development environment construction in Docker
  • 7.7 How customers can update docker images in the future
8.ROS basic course
  • 8.1 ROS introduction
  • 8.2 ROS installation
  • 8.3 ROS common command tools
  • 8.4 ROS workspace
  • 8.5 ROS function package
  • 8.6 ROS node
  • 8.7 ROS topic publisher
  • 8.8 ROS topic subscribers
  • 8.9 ROS service client
  • 8.10 ROS service server
  • 8.11 ROS action client
  • 8.12 ROS action server
  • 8.13 ROS custom message reception
  • 8.14 ROS-launch file
  • 8.15 ROS-TF transformation
  • 8.16 ROS parameter service
  • 8.17 ROS-rviz use
  • 8.18 ROS-rqt tool usage
  • 8.19 Topic message recording and playback
  • 8.20 urdf model introduction
  • 8.21 gazebo introduction
  • 8.22 ROS distributed communication
9.OpenCV courses
  • 9.1 Getting started with Open Source CV
  • 9.2 Geometric transformation
  • 9.3 Image processing and draw
  • 9.4 Image beautification
  • 9.5 Opencv application
  • 9.6 AR vision
  • 9.7 AR QR code
  • 9.8 ROS+Opencv foundation
  • 9.9 ROS+Opencv application
  • 9.10 Data transformation
  • 9.11 MediaPipe development
10.Robot control course
  • 10.1 PID algorithm theory
  • 10.2 Robot PID debugging
  • 10.3 Robot information release
  • 10.4 Robot keyboard control
  • 10.5 Robot handle control
  • 10.6 Robot state estimation
  • 10.7 Robot calibration
  • 10.8 Robot URDF model
11.Depth camera course
  • 11.1 How to use the Astra camera
  • 11.2 Astra camera calibration
  • 11.3 Astra Color Tracking
  • 11.4 Astra Object Tracking
  • 11.5 Visual tracking autopilot
  • 11.6 Pure visual 2D mapping
  • 11.7 RTAB-Map 3D mapping
  • 11.8 ORB_SLAM2 basics
  • 11.9 ORB_SLAM2_Octomap
12.Lidar course
  • 12.1 Lidar basic-SLAM
  • 12.1 Lidar basic-EAI
  • 12.2 Lidar avoiding
  • 12.3 Lidar guard
  • 12.4 Lidar follow
  • 12.5 Patrol game
  • 12.6 gmapping mapping algoritm
  • 12.7 hector mapping algorithm
  • 12.8 karto mapping algorithm
  • 12.9 cartographer mapping
  • 12.10 rrt_exploration mapping
  • 12.11 AMCL
  • 12.12 Navigation and avoiding
  • 12.13 APP mapping and navigation
13.Multi-robot control course
  • 13.1 Multi-machine handle control
  • 13.2 Multi-machine navigation
  • 13.3 Multi-machine formation
  • 13.4 Multi-machine surround
14.Deep learning courses
  • 14.1 KNN recognizes handwritten
  • 14.2 Basic use of TensorFlow
  • 14.3 Basic use of PyTorch(jetson)
  • 14.4 yolov5 model training(jetson)
  • 14.5 yolov5+tensorrt acceleration
  • 14.6 yolov4-tiny
15.Voice control courses
  • 0. How to use old voice module in new image
  • 15.1 Introduction of voice control-new
  • 15.2 Voice control module port-new
  • 15.3.Introduction of voice module-old
  • 15.4.Voice control module port binding-old
  • 15.5 Voice control car movement
  • 15.6 Voice control Autopilot
  • 15.7 Voice control color recogzition
  • 15.8 Voice control color tracking
  • 15.9 Voice control multi-point nagavation
16.Robotic arm control course
  • 16.1 MoveIt configuration
  • 16.2 MoveIt control the real machine
  • 16.3 MoveIt moves randomly
  • 16.4 MoveIt kinematics design
  • 16.5 MoveIt cartesian path
  • 16.6 MoveIt avoiding
  • 16.7 MoveIt scene design
  • 16.8 MoveIt trajectory planning
  • 16.9 Mediapipe palm control car
  • 16.10 Mediapipe gesture control robotic arm
  • 16.11 Mediapipe gesture control car
  • 16.12 Mediapipe arm attitude control robotic arm
  • 16.13 Mediapipe recognizes and tracks palm control robotic arm
  • 16.14 Recognizes color block and handling
  • 16.15 Autopilot to clear obstacles
17.Voice control robotic arm course
  • 17.1 Voice control robotic arm movement
  • 17.2 Voice control robotic arm learning
  • 17.3 Voice control color block transport
  • 17.4 Voice control robotic arm grip objects
  • 17.5 Voice control robotic arm garbage sorting
18.Model training Autopilot
  • 18.0 ReadMe
  • 18.1 yolov5 to train traffic signs
  • 18.2 TensorRt acceleration identification mark
  • 18.3 Road sign indication function description
  • 18.4 Collect data
  • 18.5 Training model
  • 18.6 Model transformation and application
  • 18.7 AI Autopilot
19.For Orin-Remote control course
1. APP control
  • 1. APP control
  • 2. Model aircraft control
  • 3. Handle control
2. Model aircraft control
3. Handle control
20.Orin-Hardware course
  • 1. About expansion board_V1.0
  • 1. About expansion board_V2.0
  • 2. STM32 Development environment
  • 3. Button control
  • 4. FreeRTOS application
  • 5. Serial communication
  • 6. SBUS model aircraft remote control
  • 7. CAN bus communication
  • 8. RGB colorful light bar
  • 9. Timer interrupt to control PWM servo
  • 10. Control serial port servos
  • 11. Nine-axis attitude sensor to obtain data
  • 12. Control motor
  • 13. Timer captures the encoder data
  • 14. Robot kinematics analysis theory
  • 15. PID control robot movement
21.Orin-Basic course
  • 1. Update the firmware
  • 2. Turn off the self-starting process at startup
  • 3. Install the Rosmaster driver library
  • 4. Buzzer whistle
  • 5. Control PWM servo
  • 6. RGB colorful light bar special effects display
  • 7. Control motor
  • 8. Control robot movement
  • 9. Control Serial Servo
22.Orin-Linux operating systemnew
  • 1. Virtual machine installation and use
  • 2. Linux basics
  • 3. Remote control
  • 4. Multi-machine communication configuration
  • 5. Static IP and hotspot mode
  • 6. Bind the device ID
  • 7. Web page real-time monitoring
  • 8. Expansion tutorial
  • 9.1 Jetson Nano write sytem
  • 9.2 Jetson Xavier NX write system
  • 9.3 Jetson TX2 NX-Orin series write system
  • 9.4 Raspberry Pi write system
  • 10.Jetpack old system upgraded to SUPER system
23.Orin-Dockernew
SUPER image uses ros environment in docker
  • 1、Docker overview and docker installationnew
  • 2、Common commands for docker image containersnew
  • 3、Docker images deeply understand and publish imagesnew
  • 4、Docker hardware interaction and data processingnew
  • 5、Enter the bot's docker containernew
  • 6、Robot development environment construction in Dockernew
23.Orin-ROS basic course
  • 1.ROS introduction
  • 2.Project file structure
  • 3.Common commands and tools
  • 4.Publisher
  • 5.Subscribers
  • 6.Customize topic messages and use
  • 7.Client
  • 8.Server
  • 9.Custom service messages and usage
  • 10.TF release and monitoring
24.Orin-OpenCV courses
  • 1. Getting started with Open Source CV
  • 2. Open Source CV geometric transformation
  • 3. Open Source CV image processing and drawing text line segments
  • 4. Open Source CV image beautification
  • 5. Opencv application
  • 6. AR vision
  • 7. AR QR code
  • 8. ROS+Opencv foundation
  • 9. ROS+Opencv application
  • 10. Data transformation and point cloud
  • 11. MediaPipe development
25.Orin-Robot control course
  • 1.PID algorithm theory
  • 2.Robot PID debugging
  • 3.Robot information release
  • 4.Robot keyboard control
  • 5.Robot handle control
  • 6.Robot state estimation
  • 7.Robot calibration
  • 8.Robot URDF model
26.Orin-Depth camera course
  • 01.How to use the Astra camera
  • 02.Astra camera calibration
  • 03.Astra Color Tracking
  • 04.Astra Object Tracking
  • 05.Visual tracking autopilot
  • 06.Pure visual 2D mapping and navigation
  • 07.RTAB-Map 3D mapping navigation
  • 08.ORB_SLAM2 basics
  • 09.ORB_SLAM2_Octomap
27.Orin-Lidar course
  • 1.Lidar basic-4ROS-EAI
  • 1.Lidar basic-SLAM
  • 2.Lidar avoiding
  • 3.Lidar guard
  • 4.Lidar follow
  • 5.Patrol game
  • 6.gmapping mapping algorithm
  • 7.hector mapping algorithm
  • 8.karto mapping algorithm
  • 9.cartographer mapping algorithm
  • 10.rrt_exploration mapping algorithm
  • 11.AMCL
  • 12.Navigation and avoiding
  • 13.APP mapping and navigation
28.Orin-Multi-robot control course
  • 1.Multi-machine handle control
  • 2.Multi-machine navigation
  • 3.Multi-machine formation
  • 4.Multi-machine surround
29.Orin-Deep learning courses
  • 1.KNN recognizes handwritten digits
  • 2.Basic use of TensorFlow
  • 3.Basic use of PyTorch(jetson)
  • 4.YOLOv11Model conversion(SUPER)new
  • 5.YOLOv11Dataset annotation(SUPER)new
  • 6.YOLOv11Model conversion + tensorrt acceleration(SUPER)new
  • 7.YOLOv11Object recognition(SUPER)new
30.Orin-Voice control courses
  • 0. How to use old voice module in new image
  • 1.1 Introduction of voice module-new
  • 1.2 Introduction of voice module-old
  • 2.1 Voice control module port binding-new
  • 2.2 Voice control module port binding-old
  • 3. Voice control car movement
  • 4. Voice control Autopilot
  • 5. Voice control color recognition
  • 6. Voice control color tracking
  • 7. Voice control multi-point navigation
31.Orin-Robotic arm control course
  • 1.MoveIt configuration(VM)
  • 2.MoveIt control the real machine(VM)
  • 3.MoveIt moves randomly(VM)
  • 4.MoveIt kinematics design(VM)
  • 5.MoveIt cartesian path(VM)
  • 6.MoveIt avoiding(VM)
  • 7.MoveIt scene design(VM)
  • 8.MoveIt trajectory planning(VM)
  • 9.Mediapipe palm control car
  • 10.Mediapipe gesture control robotic arm
  • 11.Mediapipe gesture control car
  • 12.Mediapipe arm attitude control robotic arm
  • 13.Mediapipe recognizes and tracks palm control robotic arm
  • 14.Recognizes color block and handling
  • 15.Autopilot to clear obstacles
32.Orin-Voice control robotic arm course
  • 1.Voice control robotic arm movement
  • 2.Voice control robotic arm learning
  • 3.Voice control color block transport
  • 4.Voice control robotic arm grip objects
  • 5.Voice control robotic arm garbage sorting
LLM tutorial
1.Development environment
  • 0. Model usage instructions
  • 1.Environments deployment
  • 2.Dialogue platform installation
2.Jetson Nano B01
  • 1.Qwen2 model
  • 2.TinyLlama model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.Orca Mini model
  • 6.StarCoder2 model
  • 7.DeepSeek-R1 model
  • 8.Expand LLaVA-Phi3
3.Jetson Orin NXNANO
  • 1.Llama3 model
  • 2.Qwen2 model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.WizardLM2 model
  • 6.Codellama model
  • 7.DeepSeek-R1 model
  • 8.Orca Mini model
  • 9.StarCoder2 model
  • 10.TinyLlama model
  • 11.Expand LLaVA
  • 12.Expand LLaVA-Phi3
4.Raspberry Pi 5B
  • 1.Meta AI Llama3 model
  • 2.Qwen2 model
  • 3.Phi-3 model
  • 4.Gemma model
  • 5.WizardLM2 model
  • 6.Meta AI Codellama model
  • 7.DeepSeek-R1 model
  • 8.Expand LLaVA
FAQ
  • Using your own Jetson board, car cannot start normally
Download
  • RemoteCtrl_APP(iOS/Android)
  • Mapping_APP(iOS_Android)
  • SystemFile_OrinNANOSUPER
  • SystemFile_OrinNXSUPER
  • SystemFile_RPi_NANO
  • Instruction Manual
  • Code
  • Autopilot Annex
  • VM software
  • Jetson_Boot_USB.tar.gz
  • Other_Annex_File
Download ZIP
FAQ
  • 1、How to connect OLED?
  • 2、Precautions for DIY Robotic Arm

Welcome to ROSMASTER X3 Plus repository

16.1 MoveIt configuration

1. MoveIt configuration

1. MoveIt configuration1.1. Start the program1.2. Configuration process1.2.1. Load URDF model1.2.2. Create a collision-free matrix1.2.3. Create a motion planning group1.2.3.1. Add robotic arm planning group1.2.3.2. Add gripper planning group1.2.4. Create preset poses (Robot Poses)1.2.5. Set end influence joints1.2.6. Establish ROS controller1.2.7. Add simulation1.2.8. Add 3D information (optional)1.2.9. Add author information. If you don’t add it, it will not be generated.1.2.10. Generate configuration file1.3. Detailed explanation of MoveIt configuration package1.3.1, config folder1.3.2, launch folder1.4. Configuration verification

1.1. Start the program

#Raspberry Pi 5 master needs to enter docker first, please perform this step
#If running the script into docker fails, please refer to ROS/07, Docker tutorial
~/run_docker.sh

Start roscore

xxxxxxxxxx
roscore

<PI5 needs to open another terminal to enter the same docker container

image-20240408144126098

Start MoveIT

xxxxxxxxxx
rosrun moveit_setup_assistant moveit_setup_assistant

1.2. Configuration process

1.2.1. Load URDF model

If an error [model not found] is reported when loading the model, exit MoveIt-->enter the workspace-->compile (sudo apt update)-->update the environment (source devel/setup.bash)-->start the MoveIt configuration again . The interface after startup is as follows:

0001

If you are loading the model generation configuration for the first time, click [Create New MoveIt Configuration Package]; if you are modifying the generated configuration file, click [Edit Existing MoveIt Configuration Package].

0002

Click the [Browse] button, find the URDF model file, and click [Load Files] in the lower right corner to load it.

1.2.2. Create a collision-free matrix

Collision detection is a very complex computational process. For multi-joint robotic arms or humanoid robots, the mechanical structure is complex and there are many joints, and collision detection requires a lot of spatial geometry calculations. But for rigid-body robots, collisions between some joints are impossible, such as adjacent limbs. The purpose of generating self-collision here is to tell us which joints will not collide with each other. In the subsequent collision detection algorithm, the detection between these joints can be directly skipped to improve detection efficiency.

After the model is loaded, select [Self-Collisions] and click the [Generate Collision Matrix] button.

0003

1.2.3. Create a motion planning group

Planning Group is one of the core parts of MoveIt. Click [Add Group] to add a planning group

0004

1.2.3.1. Add robotic arm planning group

If there is no [trac-ik] in the system, execute the following command to install it.

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sudo apt-get install ros-melodic-trac-ik*
  • Group Name: Create a group name and set it to [arm_group].

  • Kinematic Solver: Here we choose [trac_ik]

    Kinematics solving tool, this is responsible for solving forward kinematics (Forward Kinematics) and inverse kinematics (IK). Generally we choose KDL, The Kinematics and Dynamics Library. This is a kinematics and dynamics library that can well solve the forward and inverse kinematics problems of single-chain mechanical structures with more than 6 degrees of freedom.

    Of course, you can also use other IK Solver, such as SRV or IK_FAST, or you can even develop a new Solver yourself and insert it.

  • Kin. Search Resolution: Sampling density of joint space

  • Kin. Search TImeout: Solving time. If the equipment performance is insufficient or there is no solution within the specified time in the actual application process, the time can be increased; for example, set to [0.1], [0.01].

Click [Add Kin.Chain] to add a joint chain.

0005

Click [Expand All], select Base Link as [base_footprint], and Tip Link as [arm_link5]; click [save] to save.

0006

1.2.3.2. Add gripper planning group

Click [Add Group] to add a gripper planning group.

Create a group name and set it to [gripper_group]. There is no need to set up a kinematic solver; click [Add Links] to add the gripper link.

0007

Select the connecting rod of the clamping jaw part, click [>], the right side will be added automatically, and click [Save] to save.

0008

1.2.4. Create preset poses (Robot Poses)

Select [Robot Poses] and click [Add pose] to add a pose.

Add the robot arm posture, and set the posture name Pose Name to [up]

0009

Add [down] gesture

0010

Add [init] gesture

0011

Add the gripper [close] posture

0012

Add the gripper [open] posture

0013

1.2.5. Set end influence joints

Select [End Effectors] and set as shown below

0014

1.2.6. Establish ROS controller

Select [ROS Control] and click to automatically add the following joint trajectory

0014

1.2.7. Add simulation

Select [Simulation] and click [Generate URDF]

0015

1.2.8. Add 3D information (optional)

Select [3D Perception] and select [Point Cloud].

0016

1.2.9. Add author information. If you don’t add it, it will not be generated.

Select [Author Information] and add the following content.

0017

1.2.10. Generate configuration file

Select [Configuration Files], click [Browse], select the [x3plus_moveit_config] folder (the folder must be empty), and click the [Generate Package] button to generate the configuration file. After completion, click [Exit Setup Assistant].

0018

1.3. Detailed explanation of MoveIt configuration package

Open the [x3plus_moveit_config] folder we just created, and we find that there are two folders: config and launch.

1.3.1, config folder

  • fake_controllers.yaml: This is a virtual controller configuration file that allows us to run MoveIt without a physical robot or even any simulator (such as gazebo) opened.

  • joint_limits.yaml: This records the position, velocity and acceleration limits of each joint of the robot, which will be used in future planning.

  • kinematics.yaml: something set by the motion planning group, used to initialize the kinematics solution library

  • yahboomcar_X3plus.srdf: This is an important MoveIt configuration file.

  • ompl_planning.yaml: Here are various parameters for configuring various OMPL algorithms.

  • SRDF file: SRDF is the configuration file of moveit, used in conjunction with URDF. We can see that this is a configuration file in xml format. The root is robot and has an attribute name='yahboomcar_X3plus'. The following is what was just set in the Setup Assistant, including the definition of groups, poses, terminal controllers, virtual joints, and collision-free matrix ACM. Theoretically, as long as we have srdf and urdf, we can completely define a robot moveit information.

1.3.2, launch folder

  • demo.launch: demo is the summary point of the operation. When we open it, we can see that it includes other launch files.

  • move_group.launch: As the name suggests, the function of move group is to make a planning group move. The default is to use the ompl motion planning library. Others are to set some basic parameters and can be skipped for now.

  • planning_context.launch: Here we can see that the urdf and srdf files used are defined, as well as the kinematics solution library. It is not recommended to change these manually, but if you need to use a different urdf, srdf, you can change it here.

  • setup_assistant.launch: If you need to change some configuration, you can run it directly.

1.4. Configuration verification

Enter the workspace where the configuration file is located and execute the following command

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cd ~/yahboomcar_ws # Enter the workspace
catkin_make # compile
source devel/setup.bash # Update system environment
roslaunch arm_moveit_demo x3plus_moveit_demo.launch sim:=true # Start moveIT

Examples are as follows

0019

Voice control multi-point nagavation
MoveIt control the real machine

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