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And machines that move

Brainiacs Autonomous Race Car

A self-driving model car that reads the course’s traffic signs and steers itself, built from scratch in 20 days.

My partTeam of two, with Wassim Ghaddar

GitHub — autonomous-race-car ↗Read the write-up →

In short

A WRO Future Engineers vehicle dividing Jetson Nano perception from Arduino Mega real-time control, with OpenCV traffic-sign logic, PID steering, an MPU6050 IMU, and TCS34725 color sensing.

What it is
A dual-processor autonomous vehicle built for the 2023 World Robot Olympiad Future Engineers challenge.
Why it matters
A twenty-day build had to combine visual understanding, traffic-marker logic, obstacle avoidance, and reliable motion on limited compute and a student budget.
My part
I worked on the system architecture, computer vision, sensor integration, and embedded control, alongside my teammate Wassim Ghaddar.

Step by step

  1. 1

    See

    The Jetson Nano runs OpenCV lane and traffic-sign logic in Python. Its output is a small stream of events, not raw imagery.

  2. 2

    Decide

    A TCS34725 color sensor and MPU6050 IMU refine track- and heading-related decisions when the visual channel is uncertain or off-cadence.

  3. 3

    Steer

    The Arduino Mega closes a PID steering loop at a predictable cadence, isolating time-sensitive control from the vision pipeline’s bursty timing.

  4. 4

    Move

    Motor commands drive the physical vehicle. Chassis, wiring, and power are part of the tuning problem, not incidental to it.

Results

20 days
Build time
from scratch, as RHU reported
Third, Future Engineers
Placement
World Robot Olympiad, July 2023
>95 teams / >250 participants
Competition size
WRO Future Engineers, as RHU reported

From the project

The Brainiacs vehicle running an obstacle-course lap during a WRO Future Engineers demonstration.
The vehicle in motion, demonstrating a full obstacle-avoidance lap.
Front view of the Brainiacs vehicle showing camera, chassis, and drive wheels.
Front view — camera mounted above the drivetrain for the perception pipeline.
Full electrical schematic of the vehicle, including Jetson Nano, Arduino Mega, motor driver, IMU, and color sensor.
System schematic — perception, control, sensing, and drive on one diagram.
Team Brainiacs standing with the vehicle at the WRO Future Engineers competition venue.
Team Brainiacs at the competition venue.
For engineersHow it is built, its limits, and its keywords.

How it works

Perception runs in Python and OpenCV on a Jetson Nano and is sent as compact events to an Arduino Mega, which owns the time-sensitive steering PID and drivetrain commands. A TCS34725 color sensor and MPU6050 IMU close gaps the camera cannot handle alone.

Limits

  • Rafik Hariri University reported third place in July 2023. We were later re-ranked to second, but there is no official page for the revised standing, so this page keeps the university’s figure.
  • Twenty days only leaves so much time to optimise or document each subsystem.
  • Track and traffic-sign behavior are tied to the WRO Future Engineers 2023 environment and cannot be generalized without new testing.

Keywords

  • WRO Future Engineers
  • Jetson Nano
  • Arduino Mega
  • PID steering
  • MPU6050
  • TCS34725
  • sensor fusion

Read the write-up →

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