Defying gravity, one PID loop at a time

Meet the Self-Balancing Bot - a two-wheeled marvel that refuses to fall over! This isn't just another robot; it's a testament to the beautiful dance between physics, mathematics, and engineering. Using the magic of PID control and the precision of a BNO055 IMU, this little warrior constantly fights gravity and wins.

Our bot thinks fast and acts faster:

• 🎛️ PID Controller: The secret sauce that keeps things upright
• 📡 BNO055 IMU: 9-axis absolute orientation sensor providing real-time feedback
• 🔧 Arduino Nano: The compact powerhouse processing it all
• 🎯 Closed-Loop System: Continuous feedback for perfect balance

┌─────────────┐    ┌──────────────┐    ┌─────────────┐
│   BNO055    │───▶│ Arduino Nano │───▶│   Motors    │
│ IMU Sensor  │    │ PID Control  │    │  & Wheels   │
└─────────────┘    └──────────────┘    └─────────────┘
       ▲                   │                    │
       │                   ▼                    │
       │            ┌──────────────┐            │
       └────────────│ Tilt Angle   │◀───────────┘
                    │  Feedback    │
                    └──────────────┘

1. Sense: BNO055 measures the bot's tilt angle and angular velocity
2. Think: Arduino calculates the error using PID algorithm
3. Act: Motors adjust wheel speed to counteract the tilt
4. Repeat: Loop runs continuously at high frequency
5. Balance: Bot maintains upright position like a digital tightrope walker

• 🎪 Dynamic Balance: Recovers from disturbances automatically
• 🔄 Real-time Processing: Sub-10ms response time
• 📊 Sensor Fusion: BNO055's built-in Kalman filter for smooth data
• 🎛️ Tunable Parameters: Adjustable PID gains for optimal performance on your own bot
• 🔧 Compact Design: Nano form factor for minimal footprint

Arduino Nano          BNO055 IMU
    VIN    ────────────  VCC
    GND    ────────────  GND
     A4    ────────────  SDA
     A5    ────────────  SCL

Arduino Nano        Motor Driver
     D3     ────────────  ENA
     D4     ────────────  IN1
     D5     ────────────  IN2
     D6     ────────────  ENB
     D7     ────────────  IN3
     D8     ────────────  IN4

The art of balance lies in the PID parameters:

• Kp (Proportional): Start with 20-50, higher = more aggressive
• Ki (Integral): Usually small, 0.1-1.0, eliminates steady-state error
• Kd (Derivative): Start with 0.5-2.0, adds damping

1. Set Ki and Kd to 0
2. Increase Kp until oscillation begins
3. Add Kd to reduce oscillation
4. Add small Ki to eliminate offset

• AI Powered: Reinforcement Learning (NO magical PID!)
• Advanced Sensors: Camera for line following
• Machine Learning: Adaptive PID parameters
• LED Indicators: Visual status feedback

• Mount Arduino Nano and BNO055 on chassis
• Connect motors to H-bridge driver
• Wire according to pinout diagram above
• Install push button on pin 11 for initial calibration

• Install Adafruit BNO055 library in Arduino IDE
• Upload the provided code to Arduino Nano
• Open Serial Monitor (115200 baud) for debugging

• Power on the bot in upright position
• Wait for BNO055 auto-calibration (few seconds)
• Press calibration button to set balance point
• Observe angle readouts in Serial Monitor

• Adjust the three PID parameter sets in code
• Modify motorMax, motorMin values for your motors
• Change startAngle for different safety thresholds
• Test in safe environment with crash protection!

• Place bot upright and watch the magic
• Gently push to test recovery response
• Monitor serial output for performance analysis

Found a bug? Have an improvement? Contributions are welcome! Whether it's:

• Code optimizations
• Documentation improvements
• Hardware modifications
• PID tuning suggestions

This project is open source - feel free to learn, modify, and share!