An end‑to‑end open hardware + software autonomous race vehicle built in 20 days for the WRO Future Engineers challenge. Combines embedded control, sensor fusion, and Jetson‑powered computer vision.
| Domain | Stack |
|---|---|
| High‑Level Compute | NVIDIA Jetson Nano (Python / OpenCV) |
| Real‑Time Control | Arduino Mega + Nano (C++ / PID) |
| Perception Sensors | Raspberry Pi Cam v2.1, TCS34725 Color, MPU6050 IMU |
| Actuation | Brushless DC Motor, Geared Steering Servo, L298N Driver |
| Power | 5× 18650 Li‑Ion Cells |
Goal: Reliably detect corners & signs, execute smooth pathing with PID steering & speed modulation.
| Path | Purpose |
|---|---|
src/ |
Firmware & vision code (Arduino + Jetson) |
docs/ |
Extended documentation (hardware, software, media) |
models/ |
3D printable / CNC model files |
schemes/ |
Wiring / electronic schematic PNG |
t-photos/ |
Team photos |
v-photos/ |
Vehicle reference photos |
Project Report/ |
Formal competition project report |
CONTRIBUTING.md |
How to help extend the project |
- Jetson‑based traffic sign & marker detection pipeline.
- Deterministic Arduino control loop with PID steering stabilization using IMU feedback.
- Color sensor driven corner recognition for track turning logic.
- Modular dual‑MCU design (Mega primary, Nano auxiliary potential expansion).
- Clear calibration steps for IMU bias, color thresholds & PID tuning.
Camera --> Jetson (Python CV) --> STEER / EVENT cmds -->
+----------------------+
Color Sensor --> Arduino Mega (PID loop) -->| Motor Driver (L298N) |--> Drive Motor
IMU --> (Sensor Fusion) +----------------------+
--> Servo (Steering)
See docs/software and docs/hardware for deeper diagrams and flow descriptions.
- Jetson Nano
- Arduino Mega 2560 & Arduino Nano
- Raspberry Pi Camera v2.1
- Brushless DC Motor + Geared Steering Servo
- L298N Dual H‑Bridge Motor Driver
- MPU6050 IMU (orientation + rate for PID)
- TCS34725 Color Sensor (corner & marker detection)
- 5× 18650 Cells (regulated rails; common ground)
Full bill of materials with notes: docs/hardware/README.md.
| Component | Location | Notes |
|---|---|---|
| Vision / Sign Detection | src/Jetson Code/main.py |
OpenCV pipeline, serial out commands |
| Mega Control Firmware | src/ArduinoMegaCodeV1.0 |
Main loop: sensors, PID, actuation |
| Nano Firmware | src/ArduinoNanoCodeV1.0 |
Expansion / auxiliary logic (future) |
| Libraries Snapshot | src/Arduino Libraries/ |
Vendor libs for reproducibility |
git clone https://github.com/<your-org-or-user>/Brainiacs-Future-Engineers-2023.git
cd Brainiacs-Future-Engineers-2023- Open the
.inoin the Arduino IDE (Board: Mega 2560). - Install libraries if not auto‑resolved (color sensor, IMU, Servo). Snapshot included under
src/Arduino Libraries. - Upload and open Serial Monitor for telemetry.
Install dependencies (example):
sudo apt update
sudo apt install -y python3-opencv python3-numpy
python3 src/'Jetson Code'/main.pyReference: schemes/Schematic circuit .png and docs/hardware notes.
| Step | Purpose | Method |
|---|---|---|
| IMU Bias | Remove static drift | Average N samples at startup |
| PID Tune | Stable steering | Increase P to oscillation threshold, add D to damp |
| Color Thresholds | Reliable corner detect | Sample track under lighting, store RGB/temperature |
| Vision Thresholds | Clean sign detection | Adjust HSV / contour filters on sample frames |
See gallery in v-photos/ & team in t-photos/.
Guidelines in CONTRIBUTING.md. PRs welcome—focus on clarity, reproducibility & incremental improvements.
This project is licensed under the MIT License – see the LICENSE file for details.
Built by Team Brainiacs for WRO Future Engineers 2023. Thanks to the open‑source community and library authors whose work accelerated development.
The project was rapidly developed in 20 days integrating PID steering, color-based corner detection, and Jetson Nano computer vision for traffic sign interaction. Documentation has since been reorganized for clarity and future contributions.