yahboom
HomeLearn
Solution
Blog
Online Store
About Us
EN/中文
MicroROS Self-balancing Robot Car📖
01.Introduction
  • 0.Unboxing and Reviewing
  • 1. Must read before use - learning route
  • 2. Introduction to LiDAR
  • 3. Balance car interface description
  • 4. Analysis of common problems
  • 5. Robot charging and battery precautions
02.Assembly tutorial
  • Robot assembly steps
03.Preparation
  • 0.Quick Start (Must Read)
  • 1.Write firmware
  • 2.How to install and use VM
  • 3.ESP32 communication board configuration parameters
  • 4.Connect to microROS agent
04.ROS-WiFi module configuration
  • 0.Serial port configuration WiFi instructions
  • 1.Use ROS-WiFi cam module(must read)
  • 2.Connect to ROS-WiFi cam module agent
  • 3.Camera image correction (optional)
05.Quick start control
  • 1.Keyboard remote control
  • 2.Handle remote control
06.ROS+OpenCV course
  • 1.OpenCV Getting started
  • 2.Geometric transformation
  • 3.Image processing and drawing text line segments
  • 4.Image beautification
07.Mediapipe course
  • 1. Hand detection
  • 2. Posture detection
  • 3. Overall inspection
  • 4. Face detection
  • 5. Face recognition
  • 6. Facial effects
  • 7. 3D object recognition
  • 8. Brush
  • 9. Finger control
  • 10. Gesture recognition
08.Robot basic course
  • 1.Robot information release
  • 2.Robot keyboard control
  • 3.Robot handle control
  • 4.Robot state estimation
  • 5.Line speed calibration
  • 6.Angular velocity calibration
  • 7.Robot URDF model
09.Lidar course
  • 1.Lidar avoid
  • 2.Lidar following
  • 3.Lidar guard
  • 5.Gmapping mapping
  • 6.Cartographer mapping
  • 7.Navigation2 navigation avoid
  • 8.Navigation2 fast relocation navigation
  • 9.ROS Robot APP mapping
  • 10.ROS Robot APP navigation
10.Robot visual interaction
  • 1.Color tracking
  • 2.Object recognition and tracking
  • 3.Face recognition tracking
  • 4.Autonomous driving line patrol
  • 5.QR code motion control
  • 6.Gesture control car movement
  • 7.Palm control car movement
  • 8.Gesture control car action group
  • 9.Palm recognition and tracking
  • 10.Human body posture recognition and tracking
11.Multi-machine course
  • 1.Multi-machine handle control
  • 2.Multi-machine keyboard control
  • 3.Multi-machine navigation
  • 4.Multi-machine rapid relocation navigation
12.STM32 balancing case
01.Environment construction and development
  • 13.Window Watchdog (WWDG)
  • 01.MDK-ARM installation
  • 02.STM32CubeIDE installation
  • 03.Common driver installation
  • 04.Download the program
  • 05.MDK-ARM project usage
  • 06.Program simulation
02.STM32 getting started course
  • 01.Project creation
  • 02.LED Control(GPIO)
  • 03.Buzzer control(GPIO)
  • 04.Button control(EXTI)
  • 05.Serial communication(USART)
  • 06.Voltage detection(ADC)
  • 07.Basic timer(TIM)
  • 08.Universal timer(TIM)
  • 09.Advanced Timer(TIM)
  • 10.I2C Communication(I2C)-OLED
  • 11.SPI communication(SPI)-2.4G handle
  • 12.Independent Watchdog (IWDG)
  • 14.DMA-USART
  • 15.DMA-I2C
03.STM32 expansion course
  • 01.Battery voltage detection (ADC)
  • 02.Ultrasonic module-measuring distance (TIM)
  • 03.Motor drive+encoder (TIM)
  • 04.OLED Data-Display(I2C)
  • 05.MPU6050-Data Read (I2C)
04.Robot car PID control course
  • 01.PID basic concept
  • 02.PID example analysis
  • 03.P, PI, PD controller theory
  • 04.Position PID
  • 05.Incremental PID
  • 06.Cascade PID
  • 07.Balance principle of car
  • 08.Car upright control (PD)
  • 09.Car speed ​​control (PI)
  • 10.Car steering control (PD)
  • 11.Got angle and angular velocity (DMP algorithm)
  • 12.Got angle and angular velocity (Kalman filter algorithm)
  • 13.Got angle and angular velocity(Complementary filter algorithm)
05.Robot car basic course
  • 01.Car parameter adjustment
  • 02.Ultrasonic obstacle avoidance
  • 03.Ultrasonic follow
  • 04.Bluetooth remote control
  • 05.Load balance
  • 06.Radar obstacle avoidance
  • 07.Radar guard
  • 08.Radar follow
  • 09.Radar patrol
  • 10.Radar wall following go in a straight line
  • 11.Radar tracking wall multiple walls
06.Robot car LQR control
  • Balance car LQR high-level control
07.Circuit design
  • 01.Overall circuit design
  • 02.STM32 minimum system
  • 03.Serial port circuit design
  • 04.Power circuit design
  • 05.MPU6050 Circuit Design
  • 06.Motor drive circuit design
08.Mathematical model
  • Balance car mathematical model
13.Linux basic course
  • 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.Static IP and hotspot mode
  • 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
14.Docker course
  • 1. Overview and installation
  • 2. Common commands
  • 3. Docker images deeply understand and publish images
  • 4. Docker hardware interaction and data processing
  • 5. Enter the bot's docker container
15.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
Download
  • RemoteCtrl_APP(Android)
  • Mapping_APP(iOS_Android)
  • Code
  • Hardware Information
  • software tools
  • 3D model file
  • Instruction manual
  • VM image file
  • ROS2_Basic_VM
Download ZIP

Welcome to MicroROS Self-balancing Robot Car repository

3.Robot handle control

Robot handle control

Note: The virtual machine needs to be in the same LAN as the car, and the ROS_DOMAIN_ID needs to be the same. You can check [Must-read before use] to set the IP and ROS_DOMAIN_ID on the board.

1. Program function description

Connect the car to the proxy, connect the handle's receiver to the virtual machine port, run the program, and you can use the remote control to control the car's movement and buzzer.

2. Start and connect the agent

Take the supporting virtual machine as an example, enter the following command to start the agent,

xxxxxxxxxx
sudo docker run -it --rm -v /dev:/dev -v /dev/shm:/dev/shm --privileged --net=host microros/micro-ros-agent:humble udp4 --port 8899 -v4

image-20241226101427280

Then, turn on the car switch and wait for the car to connect to the agent. The connection is successful as shown in the figure below,

image-20241226101559446

3. Start the program

To connect the virtual machine to the controller receiver, you need to ensure that the virtual machine can recognize the controller receiver. If it is connected as shown in the figure below,

image-20231220112453720

If it is not connected, check [Virtual Machine] -> [Removable Devices] in the menu bar on the virtual machine toolbar to check whether [DragonRise Controller] is checked.

3.1 Run command

Take the matching virtual machine as an example, input in the terminal,

Start the chassis driver,

xxxxxxxxxx
ros2 launch yahboomcar_bringup yahboomcar_bringup_launch.py

Open another terminal and input,

xxxxxxxxxx
ros2 launch yahboomcar_ctrl yahboomcar_joy_launch.py ••#Handle remote control car program

Observe the handle indicator light, if it is always on, it means the connection is successful. After the program starts, press [START] and the car buzzer will sound. Press the R1 key, and the terminal prints the following information, turning on the handle control. You can use the left joystick to control the car forward and backward; you can use the right joystick to control the car left and right;

xxxxxxxxxx
[yahboom_joy-2] [INFO] [1735197789.731509428] [joy_ctrl]: Play:true

The remote control button description is as follows:

  • Left joystick: front and back directions are valid, controlling the car forward and backward, and left and right directions are invalid

  • Right joystick: left and right directions are valid, controlling the car to turn left and right, and front and back directions are invalid

  • START button: buzzer control

  • R1 button: handle control speed switch, press it to control the car speed with the remote control, press it again to lose the handle control speed, and it is also a play switch, press it to stop, press it again to continue running the function play program, including radar obstacle avoidance, radar guard, etc.

  • MODE button: switch mode, use the default mode, after switching the mode, if the key value is incorrect, the program will report an error and exit.

4. Node communication graph

Terminal input,

xxxxxxxxxx
ros2 run rqt_graph rqt_graph

image-20241227160955790

If it is not displayed at first, select [Nodes/Topics(all)] and click the refresh button in the upper left corner.

5. Code analysis

Source code reference path (taking the supporting virtual machine as an example),

xxxxxxxxxx
/home/yahboom/yahboomcar_ws/src/yahboomcar_ctrl/yahboomcar_ctrl

yahboom_joy.py

xxxxxxxxxx
#!/usr/bin/env python
# encoding: utf-8

#public lib
import os
import time
import getpass
import threading
from time import sleep

#ros lib
import rclpy
from rclpy.node import Node
from geometry_msgs.msg import Twist
from sensor_msgs.msg import Joy
from actionlib_msgs.msg import GoalID
from std_msgs.msg import Int32, Bool, UInt16

class JoyTeleop(Node):
    def __init__(self, name):
        super().__init__(name)
        self.Joy_active = False
        self.Buzzer_active = 0
        self.cancel_time = time.time()
        self.user_name = getpass.getuser()
        self.linear_Gear = 1.0 / 2
        self.angular_Gear = 1.0 / 2
        
        # create pub
        self.pub_goal = self.create_publisher(GoalID, "move_base/cancel", 10)
        self.pub_cmdVel = self.create_publisher(Twist, 'cmd_vel', 10)
        self.pub_Buzzer = self.create_publisher(UInt16, "beep", 1)
        self.pub_JoyState = self.create_publisher(Bool, "JoyState", 10)
        
        # create sub
        self.sub_Joy = self.create_subscription(Joy, 'joy', self.buttonCallback, 10)
        
        # declare parameter and get the value
        self.declare_parameter('xspeed_limit', 1.0) # 25 
        self.declare_parameter('yspeed_limit', 1.0)
        self.declare_parameter('angular_speed_limit', 3.0) # 300 
        self.xspeed_limit = self.get_parameter('xspeed_limit').get_parameter_value().double_value
        self.yspeed_limit = self.get_parameter('yspeed_limit').get_parameter_value().double_value
        self.angular_speed_limit = self.get_parameter('angular_speed_limit').get_parameter_value().double_value 
        
    def buttonCallback(self, joy_data):
        if not isinstance(joy_data, Joy): return
        self.user_jetson(joy_data)
        
    def user_jetson(self, joy_data):
        # cancel nav
        if joy_data.buttons[7] == 1:
               self.cancel_nav()
        # Buzzer
        if joy_data.buttons[11] == 1:
            b = UInt16()
            self.Buzzer_active = not self.Buzzer_active
            b.data = self.Buzzer_active 
            self.pub_Buzzer.publish(b)
                
        xlinear_speed = self.filter_data(joy_data.axes[1]) * self.xspeed_limit * self.linear_Gear
        angular_speed = self.filter_data(joy_data.axes[2]) * self.angular_speed_limit * self.angular_Gear
        if xlinear_speed > self.xspeed_limit: xlinear_speed = self.xspeed_limit
        elif xlinear_speed < -self.xspeed_limit: xlinear_speed = -self.xspeed_limit
        if angular_speed > self.angular_speed_limit: angular_speed = self.angular_speed_limit
        elif angular_speed < -self.angular_speed_limit: angular_speed = -self.angular_speed_limit
        twist = Twist()
        twist.linear.x = xlinear_speed
        twist.linear.y = 0.0
        twist.angular.z = angular_speed
        if self.Joy_active == True:
            self.pub_cmdVel.publish(twist)
  
    def filter_data(self, value):
        if abs(value) < 0.2: value = 0
        return value
    
    def cancel_nav(self):
        now_time = time.time()
        if now_time - self.cancel_time > 1:
            Joy_ctrl = Bool()
            new_Joy_active = not self.Joy_active
            if new_Joy_active != self.Joy_active:
                if new_Joy_active:
                    self.get_logger().info("Play:true")
                else:
                    self.get_logger().info("Play:false")
            self.Joy_active = new_Joy_active
            Joy_ctrl.data = self.Joy_active
            for i in range(3):
                self.pub_JoyState.publish(Joy_ctrl)
                self.pub_cmdVel.publish(Twist())
            self.cancel_time = now_time

6. Variables corresponding to remote control key values

Based on the default mode [Controller], the key values ​​corresponding to the remote control are as follows,

Remote control eventCorresponding variable
Left joystick upaxes[1]=1
Left joystick downaxes[1]=-1
Right joystick leftaxes[2]=1
Right joystick rightaxes[2]=-1
Button X pressedbutton[3]=1
Button B pressedbutton[1]=1
Button Y pressedbutton[4]=1
R1 button pressedbutton[7]=1
Start button pressedbutton[11]=1
Left joystick pressedbutton[13]=1
Right joystick pressedbutton[14]=1

Combined with the source code above, it is easy to understand. When these values ​​change, it means that the remote control is pressed and the corresponding program can be executed. To view other button presses, you can subscribe to the /joy topic and enter in the terminal.

ros2 topic echo /joy

image-20231220141805260

Robot keyboard control
Robot state estimation

COMPANY

  • About us
  • Team Style
  • Blog

LEARNING & EXPLORATION

  • Tutorials
  • Edge AI hardware
  • Educational robots
  • Embedded intelligent hardware

WHERE TO BUY

  • Yahboom Online Store
  • Amazon
  • Alibaba
  • AliExpress
  • Mercado

TECHNOLOGY SUPPORT

  • Email: support@yahboom.com

BE A DISTRIBUTOR

  • Email: sales@yahboom.com
QR Code

Copyright © 2017-2026 Yahboom. All Rights Reserved.

EN/中文