Yahboom STM32 Self-balancing Robot Car Kit, 4KG Load, STM32F103RCT6, 6-Axis IMU, OLED, BT 5.0

Overview

The STM32 self-balancing robot car is a robot car learning and experimentation platform based on the STM32 microcontroller for robotics and control systems exploration. It integrates an STM32F103RCT6 main control, a 6-axis IMU attitude sensor (accelerometer + gyroscope), high-power reduction motors, and a metal chassis, enabling real-time tilt sensing and balance stabilization using PID control. The platform supports a maximum load of 4KG and provides an OLED display plus a mobile APP for debugging and control (only supports Android, not iOS). Multiple expansion styles are supported to combine with various sensors.

Key Features

• Equipped with STM32F103RCT6 chip
• AB phase speed encoder
• High power DC motor
• With battery protection box
• Adjust parameters on APP
• PID and LQR control
• 6-axis IMU attitude sensing
• Low voltage warning
• Balance car mathematical model
• Ultrasonic avoiding/following functions (via ultrasonic module)
• OLED data display (supports displaying current mode and voltage)
• Posture recognition (6-axis IMU can start balance when placed on ground; can shut down balance when lifted vertically in an upright state)
• Climbing capability: slopes of about 30°

Optional expansion functions (depending on kit/modules)

• Lidar walking along the wall (Optional)
• Lidar avoiding/following (Optional)
• Lidar guard (Optional)
• K210 QR code control (Optional)
• K210 color line patrol (Optional)
• K210 color following (Optional)
• K210 self-learning (Optional)
• K210 number recognition (Optional)

Specifications

Main controller (MCU)

STM32F103RCT6 is described as a high-performance 32-bit MCU with up to 256KB Flash and 48KB SRAM, providing 51 programmable input/output pins for complex applications such as robot control systems and self-balancing robot car control systems.

Chassis

Motor parameters

Encoder parameters

Load capacity

Control & posture algorithms (as provided)

• Control algorithm: PID/LQR
• Posture algorithm: Kalman filter / complementary filter / DMP

Encoder motor wiring (PH2.0 6Pin)

APP Control (Android only)

The APP control program has been written before shipped. It contains up to 20 functions and gameplays. No need to download the program; it can be used right away. Turn the wheels gently to switch the robot car to different function modes.

Main control interface (labels)

1. Bluetooth switch
2. Gravity display
3. Motor speed display
4. Ultrasonic distance display
5. Main control interface button
6. Battery voltage display
7. Rotate right
8. Rotate left
9. Left-right motor speed display
10. Three control method: button, gravity, rocker

• Button control: Press up, down, left, and right to activate, release to stop.
• Gravity sensor: Control robot car to move forward, backward, left, and right according to the phone's posture.
• Rocker control: Push the circle in the middle to different directions to control robot car movement.

PID debugging interface (labels)

1. Balance loop parameter D
2. Balance loop parameter P
3. Speed loop parameter I
4. Speed loop parameter P
5. Steering loop parameter D
6. Steering loop parameter P
7. PID debugging interface button
8. Restore default
9. Update steering loop PID
10. Update speed loop PID
11. Update balance loop PID
12. Query PID

The PID debugging function can update the car PID data and display it on the APP interface, and can also adjust the PID parameters and restore the default parameters with one click.

Waveform display interface

Supports simultaneous display of multi-channel waveforms. Waveform details can be zoomed in and out, and the motion status of the robot car can be observed on a mobile phone.

Function modes list (as provided)

What's Included

Various kits are available. The following kit contents are provided as stated.

Standard Kit

• STM32 self-balancing robot car
• Ultrasonic module
• OLED display
• BT 5.0 module

Standard Kit functions description: PID parameter adjustment, posture recognition, load balancing, climbing, mobile phone APP remote control, ultrasonic obstacle avoidance and following functions.

Line Tracking Kit

• Standard Kit
• 4-channel tracking module
• Wire + screw package

Line Tracking Kit notes: Suitable for black line tracking with a width of 1.6~2CM, and supports high-difficulty line tracking such as right-angle turns and intersections.

Handle Control Kit

• Standard Kit
• PS2 handle
• AAA battery
• PS2 adapter board
• PS2 handle receiver
• Wire + screw package

Handle Control Kit notes: Can realize 2.4G wireless handle remote control.

K210 Vision Kit

• Standard Kit
• K210 vision module
• Hinge mounting plate
• Damping hinge plate
• K210 adapter
• Screw package
• TF card
• Card reader

K210 Vision Kit notes: Can realize visual recognition and interactive functions such as visual following, visual line tracking, QR code control and other functions.

Lidar Kit

• Standard Kit
• T-MINI PLUS lidar
• Wire + screw package

Lidar Kit notes: Based on lidar ranging functions, lidar guarding, obstacle avoidance, following, patrolling and other gameplay can be realized.

For help choosing the right kit and accessories, contact support@rcdrone.top or visit https://rcdrone.top/.

Applications

• Robotics education and classroom demonstrations
• Control algorithm learning (PID / LQR) and parameter debugging
• Sensor expansion experiments (ultrasonic, infrared line tracking, 2.4G wireless handle, K210 vision module, lidar)

Manuals

Tutorial link

STM32 Self-balancing Robot Car

Code analysis video tutorial with English subtitles (as listed)

• Environment construction and development
  • 1.1 MDK-ARM installation.mp4
  • 1.2 STM32CubeIDE installation.mp4
  • 1.3 Common driver installation.mp4
  • 1.4 Download the program.mp4
  • 1.5 MDK-ARM project usage.mp4
  • 1.6 Program simulation.mp4
  • 1.7 VSCode install.mp4
• STM32 expansion course
  • 3.1 Battery voltage detection (ADC).mp4
  • 3.2 Ultrasonic module-measuring distance (TIM).mp4
  • 3.3 Motor drive+encoder (TIM).mp4
  • 3.4 OLED Data-Display(I2C).mp4
  • 3.5 MPU6050-Data Read (I2C).mp4
  • 3.6 Bluetooth module-Data reading (USART).mp4
  • 3.7 2.4G handle-control module reading (SPI).mp4
  • 3.8 Tracking module-Read status (GPIO).mp4
  • 3.9 CCD module-Reading data (ADC).mp4
  • 3.10 Electromagnetic module-Reading data (ADC).mp4
  • 3.11 K210 module-Serial communication (USART).mp4
  • 3.12 Tmini-Plus lidar-Reading data (USART).mp4
• Robot car PID control course
  • 4.1 PID basic concept.mp4
  • 4.2 PID example analysis.mp4
  • 4.3 P, PI, PD controller theory.mp4
  • 4.4 Position PID.mp4
  • 4.5 Incremental PID.mp4
  • 4.6 Cascade PID.mp4
  • 4.7 Balance principle of car.mp4
  • 4.8 Car upright control (PD).mp4
  • 4.9 Car speed control (PI).mp4
  • 4.10 Car steering control (PD).mp4
  • 4.11 Got angle and angular velocity (DMP algorithm).mp4
  • 4.12 Got angle and angular velocity (Kalman filter algorithm).mp4
  • 4.13 Got angle and angular velocity (Complementary filter ...)
• Robot car basic course
  • 5.1 Car parameter adjustment.mp4
  • 5.2 Ultrasonic obstacle avoidance.mp4
  • 5.3 Ultrasonic follow.mp4
  • 5.4 Bluetooth remote control.mp4
  • 5.5 Load balance.mp4
• Robot car advanced course
  • 6.1 4-channel tracking.mp4
  • 6.2 4-channel tracking avoid.mp4
  • 6.3 2.4G handle control.mp4
  • 6.4 CCD tracking.mp4
  • 6.5 CCD tracking avoid.mp4
  • 6.6 Electromagnetic tracking.mp4
  • 6.7 K210-QR code recognition.mp4
  • 6.8 K210-Color line tracking.mp4
  • 6.9 K210-Color follow.mp4
  • 6.10 K210-Self learning.mp4
  • 6.11 K210-Number recognition.mp4
  • 6.12 Lidar avoid.mp4
  • 6.13 Lidar guard.mp4
  • 6.14 Lidar follow.mp4
  • 6.15 Lidar patrol.mp4
  • 6.16 Lidar wall tracking-straight line.mp4
  • 6.17 Lidar wall tracking-multiple walls.mp4
  • 6.18 DIY Automatic driving car.mp4

Details

A compact STM32-based self-balancing robot platform designed for control-system learning, tuning, and sensor expansion.

An overview of the platform’s control hardware, sensors, and core balancing features, plus a market comparison for quick selection.

Step-by-step learning resources cover environment setup, expansion lessons, PID tuning, and progressive robot courses.

Choose the standard kit for core balancing plus ultrasonic functions and on-device status display.

Add the line-tracking kit to follow black tape routes and handle right-angle turns and intersections.

The handle control kit enables wireless PS2-style remote driving and speed control.

The K210 vision kit opens up AI-style interactions such as QR control, color tracking, and visual following.

Upgrade to lidar for advanced navigation behaviors like following, obstacle avoidance, and guarding modes.

Built around an STM32F103RCT6 MCU to support real-time balance control and rich peripheral expansion.

A rigid metal chassis and encoder motors provide stable feedback for balance control and speed measurement.

Motor construction details and wiring guidance help with assembly, troubleshooting, and control experiments.

An Android app supports parameter adjustment and switching among multiple motion and sensor modes.

Control, PID tuning, and waveform visualization are organized into dedicated app screens for faster debugging.

Core functions include posture recognition, up to 4 kg load capacity, climbing ability, ultrasonic avoidance, and OLED readouts.

The Yahboom STM32 self-balancing robot car supports LiDAR-based wall following, obstacle avoidance, patrol, guard, and follow behaviors.

The Yahboom STM32 self-balancing robot car supports line tracking, color following, QR code control, and visual recognition tasks for interactive projects.

The Yahboom STM32 self-balancing robot uses a modular controller board with Bluetooth, ultrasonic sensing, OLED display, and an MPU6050 gyro module for tuning and PID learning.

The Yahboom STM32 self-balancing robot kit supports add-on sensor accessories and includes a two-wheel chassis, camera module, and gamepad-style controller.

Mathematical modeling notes and PID/LQR control source code support tuning and control development for the STM32 self-balancing robot.

The Yahboom STM32 self-balancing robot is paired with downloadable source code folders, including library function and HAL versions for development.

The Yahboom STM32 self-balancing robot includes a detailed function development manual and BSP driving database document to support coding and setup.

Yahboom STM32 self-balancing robot code supports DMP, Kalman filter, and complementary filter options for angle acquisition and tuning.

The Yahboom STM32 self-balancing robot course materials outline step-by-step lessons on assembly, STM32CubeIDE programming, and PID tuning.

Yahboom STM32 self-balancing robot documentation includes organized tutorial folders and video lessons to guide setup and programming.

The STM32 self-balancing robot uses a metal chassis with an enclosed battery box, anti-skid wheels, and modular expansion and sensor boards for easy assembly.

The STM32 robot expansion board uses clearly labeled connectors for power, motors, sensors (MPU6050, ultrasonic, lidar), and programming to simplify wiring and setup.

The Yahboom STM32 self-balancing robot uses an STM32F103C8T6 controller and lists a 7.4V 2200mAh battery along with key dimensions for fit planning.

The Yahboom STM32 self-balancing robot kit includes line tracking accessories, a PS2 wireless handle set, K210 vision module parts, and T-MINI PLUS LiDAR accessories for expansion.