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GPS + IMU sensor fusion for vehicle dynamics Real-time position, velocity, and acceleration tracking on ESP32. For track days, autocross, vehicle research, and learning sensor fusion.

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Blackbox - ESP32 Vehicle Telemetry System

License: MIT Rust ESP32-C3

Real-time vehicle dynamics tracking using GPS+IMU sensor fusion. Professional-grade algorithms on $50 hardware.


What Is This?

A complete ESP32-C3 firmware that fuses GPS and IMU data to track your vehicle's position, velocity, and acceleration in real-time. Built for track day logging, vehicle dynamics research, and DIY automotive projects.

What it does:

  • Tracks position (±1m accuracy between GPS updates)
  • Measures velocity in 2D (earth frame)
  • Calculates true acceleration (gravity compensated)
  • Detects driving modes (idle, accelerating, braking, cornering)
  • Streams telemetry at 20-30Hz over WiFi
  • Built-in mobile dashboard - view live data on your phone

How it works:

  • 7-state Extended Kalman Filter fuses GPS (5Hz) and IMU (50Hz)
  • Gyro integrates yaw between GPS updates to maintain heading
  • Body-frame accelerations transformed to earth frame using current orientation
  • Zero-velocity updates eliminate IMU drift when stationary
  • Constant Turn Rate and Acceleration (CTRA) model for cornering

Why it's useful:

  • Track day data logging without $500+ commercial systems
  • Vehicle dynamics research and education
  • DIY EV/kit car development
  • Test suspension, brakes, and aerodynamics
  • Learn sensor fusion practically

Hardware Requirements

Core Components ($50 total)

Component Cost Purpose Where to Buy
ESP32-C3 DevKit $5 Main controller AliExpress, Amazon
WT901 IMU $25 9-axis motion sensor WitMotion store
NEO-6M GPS $15 Position/velocity AliExpress, Amazon
Wires + USB cable $5 Connections -

Optional Add-ons

  • WS2812 RGB LED ($2) - Visual status indicator
  • SD card module ($5) - Offline data logging (not yet implemented)
  • CAN transceiver ($10) - Read vehicle data (future feature)

Wiring Diagram

ESP32-C3 DevKitC-02          WT901 IMU               NEO-6M GPS
┌─────────────────┐          ┌──────────┐            ┌──────────┐
│                 │          │          │            │          │
│ 3V3 ────────────┼──────────┤ VCC      │            │          │
│ GND ────────────┼──────────┤ GND      │            │          │
│ GPIO19 (RX) ────┼──────────┤ TX       │            │          │
│ GPIO18 (TX) ────┼──────────┤ RX       │            │          │
│                 │          └──────────┘            │          │
│ 3V3 ────────────┼──────────────────────────────────┤ VCC      │
│ GND ────────────┼──────────────────────────────────┤ GND      │
│ GPIO4  (RX) ────┼──────────────────────────────────┤ TX       │
│ GPIO5  (TX) ────┼──────────────────────────────────┤ RX       │
│                 │                                  └──────────┘
│ GPIO8 ──────────┼── (Optional: WS2812 LED data pin)
│                 │
└─────────────────┘

Important: GPS uses hardware UART0 (the same as USB console). During GPS operation, you won't see serial output unless using a separate USB-JTAG debugger. This is by design to free up the UART for GPS.


Quick Start

Option A: Web Flasher (Easiest)

Flash directly from your browser - no toolchain required:

  1. Go to https://jctoledo.github.io/blackbox/
  2. Connect your ESP32-C3 via USB
  3. Select "Blackbox" from the dropdown
  4. Click "Connect Device" and select your serial port
  5. Click "Flash Firmware"

Requirements: Chrome, Edge, or Opera (Web Serial API)

Note: You may need to hold the BOOT button when connecting to enter flash mode.


Option B: Build from Source

1. Install Rust Toolchain

# Install Rust
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
source $HOME/.cargo/env

# Install ESP32 tools
cargo install espup cargo-espflash
espup install

# Load ESP environment (required in EVERY new terminal)
source $HOME/export-esp.sh

# Add rust-src component (required for ESP32)
rustup component add rust-src --toolchain esp

2. Clone and Configure

git clone https://github.com/jctoledo/blackbox.git
cd blackbox/sensors/blackbox

# Edit WiFi credentials
nano src/main.rs
# Change these lines:
# const WIFI_SSID: &str = "YourNetworkName";
# const WIFI_PASSWORD: &str = "YourPassword";
# const MQTT_BROKER: &str = "mqtt://192.168.1.100:1883";  // Your broker IP
# const TCP_SERVER: &str = "192.168.1.100:9000";          // Your server IP

3. Build and Flash

The project includes a .cargo/config.toml that configures everything automatically.

# Navigate to the sensor project
cd sensors/blackbox

# Load ESP environment first (in every new terminal!)
source $HOME/export-esp.sh

# Quick check (fast, no linking)
cargo check

# Build firmware
cargo build --release

# Build and flash in one command
cargo run --release

First build takes 10-20 minutes as it downloads ESP-IDF. Subsequent builds: 30s-2min.

4. Receive Telemetry

UDP Telemetry (recommended)

# In another terminal, from repo root
cd tools/python
python3 udp_telemetry_server.py

Receives 20Hz binary telemetry and displays:

[20Hz] Spd: 45.3km/h Pos:(123.4,456.7)m Vel:(+12.58,+0.32)m/s Acc:(+1.23,-0.15,+9.81)m/s² Yaw:+45° wz:+12°/s CORNER

MQTT (for status messages and debugging)

# Requires mosquitto or another MQTT broker
mosquitto_sub -h 192.168.1.100 -t 'car/#' -v

Building From Source

Prerequisites

Ubuntu/Debian Linux
# System dependencies
sudo apt-get update
sudo apt-get install -y git wget flex bison gperf python3 python3-pip \
  python3-venv cmake ninja-build ccache libffi-dev libssl-dev \
  dfu-util libusb-1.0-0 build-essential

# Rust and ESP toolchain
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
source $HOME/.cargo/env
cargo install espup cargo-espflash
espup install
source $HOME/export-esp.sh
rustup component add rust-src --toolchain esp
macOS
# Install Homebrew if needed
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

# System dependencies
brew install cmake ninja dfu-util

# Rust and ESP toolchain
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
source $HOME/.cargo/env
cargo install espup cargo-espflash
espup install
source $HOME/export-esp.sh
rustup component add rust-src --toolchain esp
Windows
  1. Install Visual Studio Build Tools (C++ development)
  2. Install Python 3
  3. Install Git
  4. Install Rust via rustup-init.exe
  5. Open PowerShell and run:
cargo install espup cargo-espflash
espup install
# Restart terminal to load environment
rustup component add rust-src --toolchain esp

Build Commands

The .cargo/config.toml file in the sensor project configures the target and build settings automatically:

# Navigate to the sensor project first
cd sensors/blackbox

# ALWAYS load ESP environment first!
source $HOME/export-esp.sh

# Quick check (no linking, fast)
cargo check

# Full build
cargo build --release

# Build and flash with monitor
cargo run --release

# Format code
cargo fmt

# Lint
cargo clippy -- -D warnings

# Clean build (if things go wrong)
cargo clean

No need to specify --target or -Zbuild-std - it's all configured!

Common Build Issues

Click to see troubleshooting

Error: "can't find crate for core" or "can't find crate for std"

This means the ESP toolchain isn't loaded or rust-src is missing:

# Solution 1: Make sure you're in the sensor directory
cd sensors/blackbox

# Solution 2: Load ESP environment
source $HOME/export-esp.sh

# Solution 3: Add rust-src component
rustup component add rust-src --toolchain esp

# Solution 4: Verify .cargo/config.toml exists
cat .cargo/config.toml
# Should contain:
# [unstable]
# build-std = ["std", "panic_abort"]

Error: "linking with riscv32-esp-elf-gcc failed"

source $HOME/export-esp.sh  # You forgot this!

Error: "CMake not found"

# Ubuntu/Debian
sudo apt-get install cmake ninja-build

# macOS
brew install cmake ninja

Error: "Permission denied" on serial port (Linux)

sudo usermod -a -G dialout $USER
# Log out and back in for group change to take effect

Build hangs or crashes

cargo clean
rm -rf ~/.espressif
espup install
source $HOME/export-esp.sh
rustup component add rust-src --toolchain esp
cargo build --release

Error: "espflash: command not found"

cargo install cargo-espflash

System Architecture

Data Flow

GPS (5Hz)           IMU (50Hz)           
   │                   │                  
   │ NMEA              │ Binary packets    
   │ sentences         │                   
   ▼                   ▼                   
┌─────────────────────────────────┐       
│   Sensor Parsers                │       
│   • Parse lat/lon/speed         │       
│   • Parse ax,ay,az,wx,wy,wz     │       
│   • Parse roll,pitch,yaw        │       
└────────────┬────────────────────┘       
             │                            
             ▼                            
┌─────────────────────────────────┐       
│   Coordinate Transforms         │       
│   • Remove gravity from accel   │       
│   • Body → Earth frame          │       
└────────────┬────────────────────┘       
             │                            
             ▼                            
┌─────────────────────────────────┐       
│   Extended Kalman Filter        │       
│   State: [x, y, ψ, vx, vy,      │       
│           bias_ax, bias_ay]     │       
│                                 │       
│   • Predict using IMU (50Hz)    │       
│   • Update using GPS (5Hz)      │       
│   • ZUPT when stationary        │       
└────────────┬────────────────────┘       
             │                            
             ▼                            
┌─────────────────────────────────┐       
│   Mode Classifier               │       
│   • Detect: IDLE, ACCEL,        │       
│     BRAKE, CORNER               │       
└────────────┬────────────────────┘       
             │                            
             ▼                            
┌─────────────────────────────────┐       
│   Binary Telemetry (20Hz)       │
│   • 67 bytes with checksum      │
│   • UDP stream                  │       
└─────────────────────────────────┘       

File Structure

blackbox/
├── sensors/
│   └── blackbox/
│       ├── .cargo/
│       │   └── config.toml       # ESP32-C3 build configuration
│       ├── src/
│       │   ├── main.rs            # Main loop and setup
│       │   ├── imu.rs             # WT901 UART parser
│       │   ├── gps.rs             # NMEA parser with warmup
│       │   ├── ekf.rs             # 7-state Extended Kalman Filter
│       │   ├── transforms.rs      # Body↔Earth coordinate math
│       │   ├── mode.rs            # Driving mode classifier
│       │   ├── binary_telemetry.rs # 67-byte packet format
│       │   ├── websocket_server.rs # Mobile dashboard & WebSocket server
│       │   ├── udp_stream.rs      # High-speed UDP client
│       │   ├── mqtt.rs            # MQTT client for status
│       │   ├── wifi.rs            # WiFi connection manager
│       │   └── rgb_led.rs         # WS2812 status LED
│       ├── Cargo.toml             # Rust dependencies
│       ├── sdkconfig.defaults     # ESP-IDF configuration
│       └── build.rs               # Build script
├── tools/
│   └── python/
│       ├── udp_telemetry_server.py  # Python receiver (UDP)
│       └── mqtt_binary_decoder.py   # Python receiver (MQTT)
└── README.md                        # This file

Key Algorithms

Extended Kalman Filter (ekf.rs)

  • 7-state vector: [x, y, ψ, vx, vy, bias_ax, bias_ay]
  • Prediction: IMU accelerations integrated to update velocity and position
  • Update: GPS position/velocity fused with Kalman gain
  • CTRA motion model when speed > 2 m/s and turning

Zero-Velocity Update (main.rs)

  • Detects stationary: |accel| < 0.18g && |yaw_rate| < 12°/s && GPS_speed < 3.5m/s
  • Forces velocity to zero
  • Estimates IMU biases from residual accelerations
  • Eliminates drift over time

Mode Detection (mode.rs)

  • IDLE: Low acceleration or below minimum speed
  • ACCEL: Longitudinal accel exceeds threshold (configurable via presets)
  • BRAKE: Longitudinal decel exceeds threshold (configurable via presets)
  • CORNER: Lateral accel AND yaw rate exceed thresholds, same sign
  • ACCEL+CORNER: Trail throttle / corner exit
  • BRAKE+CORNER: Trail braking / corner entry

Thresholds are adjustable via the dashboard's Driving Preset selector with 4 built-in profiles plus custom tuning.


Telemetry Format

Binary Packet (67 bytes)

struct TelemetryPacket {
    header: u16,        // 0xAA55 magic
    timestamp_ms: u32,
    
    ax, ay, az: f32,    // Acceleration (m/s²)
    wz: f32,            // Yaw rate (rad/s)
    roll, pitch: f32,   // Orientation (rad)
    
    yaw: f32,           // EKF yaw (rad)
    x, y: f32,          // Position (m, ENU frame)
    vx, vy: f32,        // Velocity (m/s)
    speed_kmh: f32,     // Display speed
    mode: u8,           // 0=IDLE, 1=ACCEL, 2=BRAKE, 4=CORNER, 5=ACCEL+CORNER, 6=BRAKE+CORNER
    
    lat, lon: f32,      // GPS (degrees)
    gps_valid: u8,      // 0=no fix, 1=valid
    
    checksum: u16,      // Sum of all bytes (excl. checksum)
}

MQTT Topics

  • car/telemetry_bin - Binary packets (if using MQTT instead of TCP)
  • car/status - JSON status messages
  • car/config - Configuration updates
  • car/gps_raw - NMEA sentences (debug only)

Configuration

WiFi and Network

Edit sensors/blackbox/src/main.rs:

const WIFI_SSID: &str = "YourNetwork";
const WIFI_PASSWORD: &str = "YourPassword";
const MQTT_BROKER: &str = "mqtt://192.168.1.100:1883";
const TCP_SERVER: &str = "192.168.1.100:9000";

EKF Tuning

Edit sensors/blackbox/src/ekf.rs:

const Q_ACC: f32 = 0.40;    // Process noise: acceleration (m/s²)²
const Q_GYRO: f32 = 0.005;  // Process noise: gyro (rad/s)²
const Q_BIAS: f32 = 1e-3;   // Process noise: bias drift (m/s²)²

const R_POS: f32 = 20.0;    // Measurement noise: GPS position (m)²
const R_VEL: f32 = 0.2;     // Measurement noise: GPS velocity (m/s)²
const R_YAW: f32 = 0.10;    // Measurement noise: magnetometer (rad)²

Mode Detection Thresholds

Mode detection thresholds can be configured live from the mobile dashboard using the Driving Preset selector. Choose from 4 built-in presets or create custom settings:

Preset Accel Brake Lateral Yaw Min Speed Best For
Track 0.35g 0.55g 0.50g 0.15 rad/s 4.0 m/s Racing, track days
Canyon 0.22g 0.35g 0.28g 0.10 rad/s 3.0 m/s Spirited mountain roads
City 0.10g 0.18g 0.12g 0.05 rad/s 2.0 m/s Daily driving (default)
Highway 0.12g 0.22g 0.14g 0.04 rad/s 5.0 m/s Highway cruising
Custom User-defined via sliders Fine-tuning

Each threshold has an entry and exit value (hysteresis) to prevent oscillation. Exit thresholds are typically 50% of entry values.

Threshold tuning tips:

  • Too many false detections? Increase thresholds
  • Missing real events? Decrease thresholds
  • Road bumps triggering modes? Increase thresholds or check calibration

Preset Selection:

  1. Open dashboard at http://192.168.71.1
  2. Scroll to "Driving Preset" section
  3. Tap a preset button - settings apply immediately
  4. Tap "Custom" to access individual sliders for fine-tuning

Note: Mode detection requires speed > min_speed. This prevents false detection from IMU noise when stationary. Higher min_speed on Highway preset filters out parking lot maneuvers.


Performance

Metric Value
Update rate 50 Hz (IMU predict) / 5 Hz (GPS update)
Telemetry rate 20 Hz (UDP stream)
Position accuracy ±1-2m (GPS dependent)
Velocity accuracy ±0.2 m/s
Latency <20ms sensor-to-transmission
Memory usage ~50KB RAM, ~800KB flash
Power ~0.5W @ 5V

LED Status Codes

Boot Sequence (Access Point Mode)

Pattern Meaning
3 magenta blinks Boot sequence started (AP mode)
5 green blinks WiFi AP started
3 cyan blinks HTTP server ready
Yellow pulses IMU calibration in progress
Continuous red blink Critical error (WiFi AP failed)

Boot Sequence (Station Mode)

Pattern Meaning
3 blue blinks Boot sequence started (Station mode)
5 green blinks WiFi connected to network
3 magenta blinks MQTT connected
5 fast red blinks MQTT connection failed (continuing without MQTT)
3 cyan blinks UDP socket ready
Yellow pulses IMU calibration in progress
Continuous red blink Critical error (WiFi connection failed)

Main Loop (operational)

Pattern Meaning
Cyan pulse (2s cycle) GPS locked, system operational
Yellow fast blink Waiting for GPS fix
3 green-white flashes Settings changed via dashboard
3 orange blinks WiFi disconnected (repeats every 5s)
2 red blinks MQTT disconnected (Station mode only, repeats every 5s)

Note: MQTT status LED only applies to Station mode. In Access Point mode, MQTT is not used and no red blinks will occur for MQTT status.


Calibration

Proper calibration is critical for accurate mode detection. The IMU calibration measures accelerometer biases that are subtracted from all future readings.

Calibration Procedure

  1. Mount the device in its final position in the car

    • Must be rigidly attached (no wobble or vibration)
    • Orientation matters: device forward = car forward
    • Does NOT need to be perfectly level (IMU handles tilt)
  2. Park on reasonably level ground

    • Doesn't need to be perfectly flat
    • Avoid steep hills during calibration
  3. Turn OFF the engine

    • Engine vibration corrupts calibration
    • For EVs, ensure the car is in Park with no systems active
  4. Power on the ESP32

    • Wait for boot sequence LED pattern
  5. Don't touch ANYTHING during yellow LED flashing (~10 seconds)

    • The device collects 150 accelerometer samples
    • ANY movement corrupts the bias calculation
    • Keep doors closed, don't sit in the car
  6. Wait for operational state

    • Yellow fast blink = waiting for GPS lock
    • Cyan pulse = GPS locked, ready to drive

Recalibration

You can trigger recalibration from the dashboard:

  1. Open dashboard at http://192.168.71.1
  2. Stop the vehicle on level ground, engine off
  3. Tap the CLR button to reset and recalibrate

Signs of Bad Calibration

  • Mode detection triggers incorrectly (constant ACCEL or BRAKE)
  • Non-zero acceleration shown when stationary
  • Speed reads incorrectly
  • G-meter not centered when parked

Fix: Power cycle and recalibrate following the procedure above.

Tips for Best Results

Do Don't
Mount rigidly with zip ties or bracket Use velcro or loose mounting
Calibrate with engine off Calibrate while idling
Wait for full yellow LED sequence Touch car during calibration
Orient device correctly (forward = forward) Mount sideways or upside down
Recalibrate if detection seems wrong Assume it's a software bug

Mobile Dashboard

The firmware includes a built-in web dashboard that runs directly on the ESP32. No external server needed - just connect your phone and view live telemetry.

How to Use

  1. Power on the device - it creates a WiFi network called "Blackbox"
  2. Connect your phone to the "Blackbox" WiFi (password: blackbox123)
  3. Open a browser and go to http://192.168.71.1
  4. View live telemetry - data streams at ~30Hz via WebSocket

Dashboard Features

Feature Description
G-meter Real-time lateral/longitudinal G display with trail
Max G values Tracks peak L/R/Accel/Brake G-forces
Speed Current speed and session max speed
Driving mode IDLE, ACCEL, BRAKE, CORNER, or combined states (ACCEL+CORNER, BRAKE+CORNER)
Driving presets One-tap presets for Track, Canyon, City, Highway, or Custom tuning
Session timer Time since dashboard loaded
GPS status Current coordinates and fix status
Recording Capture data locally for CSV export

Controls

Action Effect
CLR button Clear max G values
Tap max speed Reset max speed only
Double-tap G-meter Reset max G values only
Preset buttons Switch driving profile (Track/Canyon/City/Highway/Custom)
Reset button Reset sliders to current preset defaults (Custom mode only)
Apply button Send custom slider values to device (Custom mode only)
REC button Start/stop recording data
Export button Download recorded data as CSV

Connection Status

The indicator in the top-right shows connection quality:

  • Blue dot + "WS" - WebSocket connected (~30Hz, best)
  • Green dot + "HTTP" - HTTP polling fallback (~15Hz)
  • Gray dot + "Offline" - No connection

WiFi Modes

The firmware supports two WiFi modes, each with different connectivity options:

Access Point Mode (Default)

Best for: Mobile use, track days, standalone operation

┌──────────────┐     WiFi: "Blackbox"      ┌──────────────┐
│   ESP32      │◄─────────────────────────►│    Phone     │
│  (creates    │     192.168.71.1:80        │  (connects)  │
│   network)   │                           │              │
└──────────────┘                           └──────────────┘
  • ESP32 creates its own WiFi network: Blackbox / blackbox123
  • Connect your phone directly to view the dashboard
  • No router or internet required
  • Data delivered via WebSocket (fast) or HTTP polling (fallback)
  • No Python tools - dashboard only

To use (default, no changes needed):

cargo build --release

Station Mode

Best for: Home testing, data logging to laptop, multiple receivers

┌──────────────┐                           ┌──────────────┐
│   ESP32      │     Your WiFi Network     │   Laptop     │
│  (connects   │◄─────────────────────────►│  (Python     │
│   to router) │                           │   tools)     │
└──────────────┘                           └──────────────┘
        │                                         │
        │              ┌──────────┐              │
        └──────────────►│  Router  │◄────────────┘
                       └──────────┘
  • ESP32 connects to your existing WiFi network
  • Telemetry sent via UDP to your laptop (high-speed, 20Hz)
  • Status messages via MQTT broker
  • Python tools can receive and log data
  • Dashboard NOT available (no web server in this mode)

To use:

# Set environment variables before building
export WIFI_MODE="station"
export WIFI_SSID="YourHomeNetwork"
export WIFI_PASSWORD="YourPassword"
export MQTT_BROKER="mqtt://192.168.1.100:1883"
export UDP_SERVER="192.168.1.100:9000"
cargo build --release

Using Python Tools (Station Mode Only)

The Python tools in tools/python/ only work in Station mode when ESP32 is on the same network as your laptop.

Setup:

# Install dependencies
cd tools/python
pip install -r requirements.txt

# Start MQTT broker (if not already running)
# On Ubuntu: sudo apt install mosquitto && sudo systemctl start mosquitto
# On macOS: brew install mosquitto && brew services start mosquitto

Receive UDP Telemetry (recommended):

python3 udp_telemetry_server.py

Output:

[20Hz] Spd: 45.3km/h Pos:(123.4,456.7)m Acc:(+1.23,-0.15)m/s² CORNER

Receive MQTT Status:

python3 mqtt_binary_decoder.py

Subscribe to raw MQTT topics:

mosquitto_sub -h localhost -t 'car/#' -v

Choosing a Mode

Feature Access Point Station
Mobile dashboard ✅ Yes ❌ No
Python tools ❌ No ✅ Yes
Needs router ❌ No ✅ Yes
Range ~30m Network dependent
Multiple receivers ❌ No ✅ Yes
Data logging to laptop ❌ No ✅ Yes

Future Enhancements

  • SD card logging for offline operation
  • Web dashboard for live visualization ✓ Built-in mobile dashboard
  • CAN bus integration for vehicle data
  • Support for external wheel speed sensors
  • Bluetooth for phone connectivity
  • Over-the-air firmware updates

Contributing

Contributions welcome! Whether it's:

  • Bug fixes
  • New sensor drivers
  • Documentation improvements
  • Performance optimizations

Open an issue or pull request on GitHub.


License

MIT License - see LICENSE for details.


Acknowledgments

Built with:

  • esp-idf-hal - Rust ESP32 HAL
  • esp-idf-svc - ESP-IDF services
  • WT901 IMU from WitMotion
  • U-blox NEO-6M GPS module

Inspired by open-source motorsport and robotics projects that prove pro-grade systems don't need pro prices.


Questions? Open an issue.

Ready to track? Start with Quick Start ↑

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GPS + IMU sensor fusion for vehicle dynamics Real-time position, velocity, and acceleration tracking on ESP32. For track days, autocross, vehicle research, and learning sensor fusion.

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