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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

4.Publisher

4 Publisher

4 Publisher 4.1 Publisher 4.2 Create workspace and topic package 4.2.1 Create a workspace 4.2.2 Compilation workspace 4.2.3 Update environment variables 4.2.4 Check environment variables 4.2.5 Create function package 4.2.6 Compile function package 4.3 create a publisher 4.3.1 Creation steps 4.3.2 C++ language implementation 4.3.3 Python language implementation

4.1 Publisher

Publisher, as the name suggests, plays the role of publishing news. The message here can be the sensor information transmitted by the lower computer to the upper computer, and then packaged and packaged by the upper computer and sent to the subscribers who have subscribed to the topic; it can also be the data of the upper computer after the operation is packaged and packaged and sent to the Subscribers to this topic.

4.2 Create workspace and topic package

4.2.1 Create a workspace

mkdir -p ~/catkin_ws/src 
cd ~/catkin_ws/src 
catkin_init_workspace 

4.2.2 Compilation workspace

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cd ~/catkin_ws/ 
catkin_make 

4.2.3 Update environment variables

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source devel/setup.bash 

4.2.4 Check environment variables

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echo $ROS_PACKAGE_PATH 

4.2.5 Create function package

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cd ~/catkin_ws/src 
catkin_create_pkg learning_topic std_msgs rospy roscpp geometry_msgs turtlesim 
#Explanation: learning_topic is the name of the function package 

4.2.6 Compile function package

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cd ~/catkin_ws 
catkin_make 
source ~/catkin_ws/devel/setup.bash 

4.3 create a publisher

4.3.1 Creation steps

  1. initialize the ROS node
  2. create a handle
  3. Register node information with ROS Master, including the topic name published, the message type in the topic, and the queue length
  4. create and initialize message data
  5. Send messages cyclically according to a certain frequency

4.3.2 C++ language implementation

  1. In the src folder of the function package, create a c++ file(the file suffix is .cpp) and name it turtle_velocity_publisher.cpp
  2. copy and paste the program code below into the turtle_velocity_publisher.cpp file
​x
/* Create a speed publisher for a baby turtle */ 
#include <ros/ros.h> 
#include <geometry_msgs/Twist.h> 
int  main(int argc, char  ** argv){ 
    
    ros::init(argc, argv, "turtle_velocity_publisher"); //ROS node initialization 
    
    ros::NodeHandle  n; //here is to create handle 

    //Create a Publisher, publish a topic named /turtle1/cmd_vel, the message type is geometry_msgs::Twist, and the queue length is 10 
    ros::Publisher  turtle_vel_pub  =  n.advertise < geometry_msgs::Twist >("/turtle1/cmd_vel", 10); 
    
    ros::Rate  loop_rate(10); //Set the frequency of the loop 

    while (ros::ok()){ 
            //Initialize the message to be published, the type must be consistent with Publisher 
        geometry_msgs::Twist  turtle_vel_msg; 
        turtle_vel_msg.linear.x  =  0.8; 
        turtle_vel_msg.angular.z  =  0.6; 
        
        turtle_vel_pub.publish(turtle_vel_msg); // publish velocity message 

        //Print the published speed content 
        ROS_INFO("Publsh turtle velocity command[%0.2f m/s, %0.2f rad/s]", turtle_vel_msg.linear.x, turtle_vel_msg.angular.z); 
        
        loop_rate.sleep(); //Delay according to the loop frequency 
    } 
    return  0; 
} 
  1. the program flow chart, which can be viewed corresponding to the content of 1.3.1

pub_c++

  1. configure in CMakelist.txt, under the build area, add the following content
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add_executable(turtle_velocity_publisher src/turtle_velocity_publisher.cpp) 
target_link_libraries(turtle_velocity_publisher ${catkin_LIBRARIES}) 
  1. Compile the code in the workspace directory
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cd ~/catkin_ws 
catkin_make 
source devel/setup.bash #Environment variables need to be configured, otherwise the system cannot find the running program 
  1. run the program
  • run roscore

    xxxxxxxxxx
    roscore 
  • Run the turtle node

    xxxxxxxxxx
    rosrun turtlesim turtlesim_node 
  • Run the publisher to continuously send the speed to the little turtle

    xxxxxxxxxx
    rosrun learning_topic turtle_velocity_publisher 
  1. Screenshot of running effect

image-20220216112046184

  1. program operation instructions
  • Enter rostopic list in the terminal to view the topic list and you will find the topic /turtle1/cmd_vel
  • We use rostopic info /turtle1/cmd_vel to find out
  • image-20220216112901207

This shows that the little turtle is a subscription to the speed topic /turtle1/cmd_vel. Therefore, the publisher keeps sending speed data. After the little turtle receives it, it starts to move according to the speed.

4.3.3 Python language implementation

  1. In the function package directory, create a new folder scripts, and then create a new python file(file suffix .py) in the scripts folder, named turtle_velocity_publisher.py
  2. copy and paste the program code below into the turtle_velocity_publisher.py file
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#!/usr/bin/env python 
# -*- coding: utf-8 -*- 
# This routine will publish turtle1/cmd_vel topic, message type geometry_msgs::Twist 

import  rospy 
from  geometry_msgs.msg import Twist 

def turtle_velocity_publisher(): 
    
    rospy.init_node('turtle_velocity_publisher', anonymous = True) # ROS node initialization 

    # Create a small turtle speed publisher, publish a topic named /turtle1/cmd_vel, the message type is geometry_msgs::Twist, and 8 represents the message queue length 
    turtle_vel_pub  =  rospy.Publisher('/turtle1/cmd_vel', Twist, queue_size = 8) 

    
    rate = rospy.Rate(10) # set the frequency of the loop 

    while  not  rospy.is_shutdown(): 
        # Initialize a message of type geometry_msgs::Twist 
        turtle_vel_msg  =  Twist() 
        turtle_vel_msg.linear.x  =  0.8 
        turtle_vel_msg.angular.z  =  0.6 

        # make an announcement 
        turtle_vel_pub.publish(turtle_vel_msg) 
        rospy.loginfo("linear is :%0.2f m/s, angular is :%0.2f rad/s", 
                turtle_vel_msg.linear.x, turtle_vel_msg.angular.z) 

        
        rate.sleep() # Delay according to the loop frequency 

if  __name__  ==  '__main__' : 
    try : 
        turtle_velocity_publisher() 
    except  rospy.ROSInterruptException : 
        pass 
  1. program flow chart

pub_py2

  1. run the program
  • run roscore

    xxxxxxxxxx
    roscore 
  • Run the turtle node

    xxxxxxxxxx
    rosrun turtlesim turtlesim_node 
  • Run the publisher to continuously send the speed to the little turtle

    xxxxxxxxxx
    rosrun learning_topic turtle_velocity_publisher.py 

Note: Before running, you need to add executable permissions to turtle_velocity_publisher.py, open the terminal in the turtle_velocity_publisher.py folder,

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sudo chmod a+x turtle_velocity_publisher.py 

All pythons need to add execute file permissions, otherwise an error will be reported!

  1. Refer to 1.3.2 for operation effect and program description.
Common commands and tools
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