EquiBot: Self-Balancing-Bot 🤖ིྀ

A self-balancing bot using ESP32, MPU6050, L293D Motor Driver and a PID controller to maintain dynamic stability. This project implements an inverted pendulum model to keep the bot upright.

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📌 Features

• Real-time tilt correction using MPU6050 sensor data.
• PID control algorithm for precise motor adjustments.
• ESP32-based implementation with efficient processing.
• DC motor control via motor driver for smooth balancing.
• Expandable for Bluetooth/WiFi remote control and advanced tuning.

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🛠 Components Used

Component	Description
ESP32	Microcontroller for processing Sensor Data
MPU6050	6-axis Motion Sensor (Accelerometer + Gyroscope)
Motor Driver	Controls the direction and speed of motors
DC Motors	Provides motion and balance adjustments
Battery	Power source for ESP32, motors, and sensors
Chassis & Wheels	Physical structure of the bot

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⚙️ Circuit Connections

MPU6050 to ESP32:

• VCC → 3.3V (ESP32)
• GND → GND (ESP32)
• SDA → GPIO21 (ESP32)
• SCL → GPIO22 (ESP32)

Motor Driver to ESP32:

• IN1, IN2 → GPIO26, GPIO27 (ESP32)
• IN3, IN4 → GPIO14, GPIO12 (ESP32)
• Enable Pins (PWM) → GPIO33, GPIO32 (ESP32)

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🔢 PID Control Implementation

The PID (Proportional-Integral-Derivative) controller ensures smooth and stable balancing by adjusting motor speed based on tilt error.

float Kp = 35.0, Ki = 0.1, Kd = 1.0;
float error, previousError, integral, derivative;

void loop() {
    int16_t ax, ay, az, gx, gy, gz;
    mpu.getMotion6(&ax, &ay, &az, &gx, &gy, &gz);
    float angle = atan2(ax, az) * 180 / PI;
    
    error = angle;
    integral += error;
    derivative = error - previousError;
    int motorSpeed = Kp * error + Ki * integral + Kd * derivative;
    
    controlMotors(motorSpeed);
    previousError = error;
    delay(10);
}

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🛠 Setup & Installation

1. Clone the repository:

   git clone https://github.com/achyuth-2308/EquiBot-Self-Balancing-Bot.git

2. Open the code in Arduino IDE or PlatformIO.
3. Install the required libraries:
   • Wire.h
   • MPU6050.h
4. Upload the code to ESP32 and power up the bot!

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🚀 Future Enhancements

• Implementing a Kalman Filter for improved sensor fusion.
• Adding Bluetooth control for remote tuning.
• Integrating an OLED display for real-time sensor data.

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🤝 Contributions

Feel free to fork, enhance, and create pull requests! Contributions are always welcome.

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📝 License

This project is open-source under the MIT License.

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📧 Contact

For any queries, reach out to me on LinkedIn or via email at achyuth2004@gmail.com.

Made with ❤️ by Achyuth Mukund and Haneef Ahmad