Real-time orientation tracking and 3D visualization using ESP32 microcontrollers and low-cost inertial measurement units such as the MPU6050 and ICM20948.
This project explores how raw IMU data can be filtered, stabilized, and transformed into an interactive digital twin in real time.
I built this project to better understand how inertial sensing systems estimate orientation in real time, and how embedded sensor data can be transformed into an intuitive visual representation of physical motion.
The goal was not to create a production-grade inertial navigation system, but rather to explore concepts such as:
- sensor fusion,
- drift and stabilization,
- coordinate systems,
- telemetry,
- and real-time visualization pipelines.
IMU Sensor (MPU6050 / ICM20948)
↓
ESP32 Data Acquisition
↓
Sensor Fusion / Filtering
↓
Serial Telemetry
↓
Processing Visualization
↓
Real-Time Digital Twin
- Real-time orientation tracking
- MPU6050 and ICM20948 support
- Complementary filter implementation
- ESP32-based processing
- Live 3D visualization
- Serial telemetry pipeline
Some of the most interesting parts of this project involved:
- reducing visible orientation drift,
- stabilizing noisy sensor data,
- handling gyro accumulation errors,
- synchronizing telemetry with visualization,
- and understanding the limitations of Euler-angle-based tracking.
These challenges became a large part of the learning process and pushed the project beyond a simple sensor demo.
/src
ESP32 sensor acquisition and filtering
/processing_sketch
Real-time 3D visualization
/media
Project media and demonstrations
A full walkthrough and explanation of the original MPU6050 implementation can be found here:
- Quaternion-based orientation tracking
- Kalman filtering
- Wireless telemetry
- Improved calibration routines
- Multi-sensor tracking
- Expanded visualization tooling
MIT License