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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

11.Got angle and angular velocity (DMP algorithm)

Got angle and angular velocity (DMP algorithm)

Got angle and angular velocity (DMP algorithm)DMP algorithmQuaternion solutionQuaternion to Euler angleQuaternionEuler angleConversion formulaSolution codeSoftware code

The tutorial introduces the use of DMP algorithm to calculate the attitude angle.

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The MPU6050 module can detect the motion data of the three-axis acceleration, the three-axis gyroscope, and the temperature data.

DMP algorithm

DMP is the motion engine inside the MPU6050, the full name of which is Digital Motion Processor. It directly outputs quaternions, which can reduce the workload of the peripheral microprocessor and avoid tedious filtering and data fusion.

Motion Driver is a software package for its motion sensors from Invensense. It is not all open source. The core algorithm part is compiled into a static link library for ARM processors and MSP430 processors, and is suitable for sensors such as MPU6050, MPU6500, MPU9150, and MPU9250.

Quaternion solution

Using the MPU6050 driver library provided by InvenSense, the raw data will be converted into quaternion output. We need to calculate the quaternion and finally get the attitude data (Euler angle): heading angle (Yaw), roll angle (Roll) and pitch angle (Pitch).

image-20240806150245483

Quaternion to Euler angle

Quaternion

Quaternion is a mathematical tool used to represent three-dimensional rotation, but it is not very intuitive to observe.

Quaternions consist of four real numbers, and the basic representation is as follows:

q=q0+q1∗i+q2∗j+q3∗k

Euler angle

Euler angle is a way to describe the rotation state of an object in three-dimensional space. It is usually composed of three angle values: yaw, roll, and pitch, which is convenient for observing posture.

Conversion formula

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pitch = asin(-2 * q1 * q3 + 2 * q0* q2)
roll = atan2(2 * q2 * q3 + 2 * q0 * q1, -2 * q1 * q1 - 2 * q2* q2 + 1)
yaw = atan2(2*(q1*q2 + q0*q3),q0*q0+q1*q1-q2*q2-q3*q3)

Solution code

MPU6050 DMP outputs the quaternion after attitude settlement, in q30 format, magnified 2^32 times (q30 = 2^32 = 1073741824).

​x
void Read_DMP(void)
{
unsigned long sensor_timestamp;
unsigned char more;
long quat[4];

dmp_read_fifo(gyro, accel, quat, &sensor_timestamp, &sensors, &more); //Read DMP data
if (sensors & INV_WXYZ_QUAT )
{
//Quaternion
q0=quat[0] / q30;
q1=quat[1] / q30;
q2=quat[2] / q30;
q3=quat[3] / q30;
Roll = asin(-2 * q1 * q3 + 2 * q0* q2)* 57.3; //Calculate the roll angle
Pitch = atan2(2 * q2 * q3 + 2 * q0 * q1, -2 * q1 * q1 - 2 * q2* q2 + 1)* 57.3; //Calculate the pitch angle
Yaw = atan2(2*(q1*q2 + q0*q3),q0*q0+q1*q1-q2*q2-q3*q3) * 57.3; //Calculate the yaw angle
}
}

Software code

Balance car PID control basics: 08-13 tutorial only provides one project file.

Product supporting materials source code path: Attachment → Source code summary → 3.PID_Course → 08-13.Balanced_Car_PID
Car steering control (PD)
Got angle and angular velocity (Kalman filter algorithm)

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