🚤 ESP32 Self-Learning Outboard Autopilot

Adaptive Trolling Autopilot for Small Boats
Powered by MicroPython, PID Control, and BNO055 Sensor Fusion

This project is a self-learning autopilot designed specifically for outboard trolling. Unlike traditional autopilots that require complex manual tuning, this system uses Passive System Identification to learn your boat's steering characteristics and automatically tunes its PID controller for optimal performance.

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✨ Key Features

• 🧠 Adaptive PID Tuning: Automatically learns your boat's responsiveness (deg/s per % power) and adjusts gains on the fly.
• 🔄 Continuous Control Loop: Runs a non-blocking 10Hz control loop for smooth, responsive steering in wind and waves.
• 🧭 9-Axis Sensor Fusion: Uses the BNO055 in NDOF mode (Quaternions) for tilt-compensated, stable heading data.
• 🌊 Sea State Estimation: Monitors roll variance to detect rough water and adapt control behavior (future expansion).
• 💾 Auto-Save: Automatically saves learned PID gains and settings to NVS memory.
• ⚡ Non-Blocking: Fully asynchronous motor control and sensor reading.

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🛠️ Hardware Setup

Component	ESP32 Pin	Notes
BNO055 SDA	GPIO 21	I2C Data
BNO055 SCL	GPIO 22	I2C Clock
Motor PWM	GPIO 27	Speed Control (0-100%)
Motor DIR	GPIO 26	Direction (High=Starboard, Low=Port)
Button	GPIO 33	Engage/Disengage (Pull-up)
LED	GPIO 19	Status Indicator

Recommended Hardware

• Controller: ESP32 DevKit V1
• Sensor: Adafruit BNO055 (or generic module)
• Motor Driver: BTS7960 (High Current) or L298N (Low Current)
• Pump: 12V Hydraulic Reversing Pump (e.g., Raymarine Type 1)

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🚀 Installation

1. Flash MicroPython: Install the latest MicroPython firmware on your ESP32.
2. Upload Files: Upload the following files to the root directory:
   • main.py: Core logic
   • lib/bno055.py: Sensor driver
   • lib/bno055_base.py: Sensor base driver
   • lib/motor.py: Motor controller
   • lib/pid.py: PID controller
   • lib/autotuner.py: Adaptive tuning logic
   • lib/gps_stub.py: GPS placeholder
3. Wiring: Connect hardware according to the table above.

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🎮 Usage

1. Calibration (First Run)

The BNO055 needs calibration.

• Power on the system.
• Rotate the sensor/boat in figure-8 motions until the system status indicates calibration (LED behavior can be added for this).
• Note: The system saves calibration data automatically.

2. Engaging Autopilot

1. Point the boat on your desired heading.
2. Press the Button (GPIO 33).
3. The LED will turn ON.
4. The system will lock onto the current heading.

3. Auto-Tuning (Passive)

• Just drive! The system starts with "Safe" default gains.
• As it makes corrections, it measures how fast the boat turns.
• If the boat is sluggish, it increases aggressiveness.
• If the boat is twitchy, it decreases aggressiveness.
• Settings are saved every 60 seconds.

4. Disengaging

• Press the Button again.
• The LED turns OFF.
• Motor stops immediately.

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📂 Project Structure

├── main.py              # Entry point & Control Loop
├── lib/
│   ├── autotuner.py     # Adaptive PID Logic
│   ├── bno055.py        # BNO055 Driver
│   ├── bno055_base.py   # BNO055 Base Class
│   ├── motor.py         # Non-blocking Motor Control
│   ├── pid.py           # PID Controller
│   └── gps_stub.py      # Future GPS Integration
└── README.md            # This file

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🔮 Future Roadmap

• GPS Integration: Connect NMEA GPS for Course Over Ground (COG) hold.
• Pattern Steering: Zig-zag and Circle modes for fishing.
• WiFi UI: Web-based configuration and monitoring.