ONE-Robot
2015年做的一个基于IMU和STM32的独轮自平衡机器人
Open-source firmware and 3D models for a self-balancing unicycle robot, using an IMU and STM32 microcontroller to stay upright like a rider leaning to balance a bicycle.
One-Robot Explanation
This is a self-balancing unicycle robot built in 2015. Imagine a device that looks like a unicycle—one wheel, standing upright on its own without falling over. The robot uses an IMU (a motion sensor that detects tilt and movement) and an STM32 microcontroller (a small computer chip) to constantly adjust its wheel speed and keep itself balanced, much like how you lean forward and backward to stay upright on a bicycle.
The repository contains the firmware code that runs on the microcontroller, plus 3D models of the mechanical parts so you could theoretically build or rebuild one yourself. The creator notes that the circuit board design is lost to time, but they say it's simple enough: essentially a basic STM32F103 setup connected to two motors (controlled with PWM signals), two sensors that read wheel rotation data from encoders, and several sensors reading raw data from the gyroscope and accelerometer. The microcontroller takes all this sensor data, runs a balancing algorithm, and sends commands to keep the wheel spinning at just the right speed to maintain balance.
This would appeal to roboticists, engineering students, and hobbyists interested in control systems and embedded programming. If you've ever wondered how a self-balancing skateboard or Segway works under the hood, this project gives you a concrete example you can study or build from. The creator has also shared a demo video showing it in action, which helps illustrate what all the code actually accomplishes in the real world.
What makes this project notable is that it's a complete, working example from someone willing to open-source both the control logic and the mechanical design. It's more educational than cutting-edge—built in 2015 using straightforward components and techniques—but that also makes it more approachable for someone learning how motion control and sensor fusion actually work in practice.
Where it fits
- Study a working example of how self-balancing devices like Segways use sensor fusion and control loops.
- Learn embedded programming by examining STM32 firmware that reads encoders, gyroscope, and accelerometer data.
- Build or rebuild the physical robot using the provided 3D models and firmware code.
- Experiment with tuning the balancing algorithm to understand motion control in practice.