BiathlONE

BiathlONE
Color Detection with path following
Cute view

Inspiration

The Winter Olympics showcase an extraordinary balance of speed, endurance, precision, and strategic decision-making. Among all events, the biathlon stood out to us as a perfect metaphor for robotics: athletes must push their physical limits while remaining calm and accurate under pressure. We were inspired to translate this challenge into an engineering context by building a robot that could move efficiently, make real-time decisions, and perform precise actions.

BiathlONE was created to embody this balance of motion and accuracy through autonomous navigation, object manipulation, and target interaction.

What it does

BiathlONE is an autonomous robot that navigates a Winter-Olympics–style course while demonstrating the three core principles of robotics: perception, reasoning, and actuation.

The robot begins by picking up a battery from the start area and placing it into a designated white zone, which determines which section of the course is unlocked.

Depending on the selected path, BiathlONE can complete either:

a precision-based target shooting challenge, or
a time-sensitive obstacle course.

Using color sensors, ultrasonic sensing, and IR sensors, the robot detects path splits, avoids obstacles, follows colored tracks, and navigates toward key zones.

In the target shooting section, BiathlONE accurately aligns itself with the center of the target and launches a ball toward a scoring area. In the obstacle course section, the robot prioritizes smooth turns, obstacle avoidance, and speed to maximize points.

How we built it

BiathlONE was built exclusively using the components provided in the hacker kit. The robot is powered by an Arduino Uno (USB-C) and mounted on a laser-cut base with a two-wheel drivetrain driven by DC motors and a motor driver.

Servo motors were used to create an articulated arm and claw capable of reliably picking up and placing batteries.

For perception, we integrated:

an ultrasonic sensor for distance measurement,
IR sensors for obstacle detection, and
a color sensor for path recognition and zone identification.

These sensors feed data into a control system that uses conditional logic and state-based decision-making to determine movement, task sequencing, and actuation. The entire system was wired on a breadboard and carefully organized to ensure stability and reliability throughout repeated runs.

Challenges we ran into

One of our biggest challenges was achieving reliable sensor readings under varying lighting conditions, particularly for color detection on the track. Small variations in ambient light significantly affected accuracy, requiring careful calibration and testing.

Mechanical stability was another challenge, especially when navigating ramps and sharp turns. Balancing weight distribution between the drive system and the arm mechanism took multiple design iterations.

Additionally, coordinating movement and object manipulation without exceeding time limits or requiring excessive reuploads demanded thoughtful logic design and debugging under pressure.

Accomplishments that we're proud of

We are proud of successfully building a fully autonomous robot that integrates multiple sensors, actuators, and decision-making logic using a limited hardware kit.

BiathlONE was able to consistently:

pick up and place batteries,
detect path splits,
navigate complex track sections, and
complete both precision and speed-based challenges.

We are also proud of our clean and sturdy build quality, organized wiring, and a design that clearly reflects the Winter Olympics theme. Most importantly, we achieved reliable performance within the competition time constraints while maintaining accuracy and control.

What we learned

Through this project, we gained hands-on experience with sensor integration, real-time decision-making, and mechanical design trade-offs.

We learned how small hardware choices can have large impacts on stability and performance, and how crucial calibration and testing are for reliable autonomy.

The project also reinforced the importance of teamwork, time management, and iterative development—especially in a fast-paced hackathon environment where rapid problem-solving is essential.

What's next for BiathlONE

With more time, we would improve BiathlONE by implementing sensor fusion techniques to further increase navigation accuracy and robustness.

We would also refine the shooting mechanism for greater consistency and explore adaptive speed control based on terrain conditions.

Future iterations could include more advanced control algorithms, improved mechanical precision, and enhanced environmental awareness to better handle unpredictable course variations. BiathlONE has strong potential to evolve into a more competitive and intelligent autonomous system.

Software Project: UTRA Bets

There is nothing like gambling after a hackathon! Players can gather around to play with fake money and bet if they think a robot will be able to hit their target.

This project is a real-time multiplayer betting game where players wager on which colored zone a white styrofoam ball will land in. The game features four concentric colored zones (BLUE, RED, GREEN, and BLACK from outermost to innermost). Players place bets through an web interface, with live updates showing all active bets and real-time statistics as the game progresses.

We use LLMs to make the gaming experience more personal. When the game concludes, the host captures a photo using their phone, and Google's Gemini AI (gemini-2.5-flash-lite) analyzes the image to determine which zone the ball landed in - eliminating human intervention. The results are automatically calculated and displayed to all players, showing winners, losers, and payout amounts based on the configured multiplier. A higher number means more risk of course!

A funny feature is the AI-powered voice commentator that uses ElevenLabs text-to-speech combined with Gemini's language model to generate unique, snarky commentary for every bet placed. The commentator makes the experience feel like a live sporting event.

We use Flask for the web backend, Socket.IO for WebSocket communication, MongoDB, OpenCV for camera integration, and ngrok for easy network accessibility. This allows players on any device - phones, tablets, or computers - to join the game from anywhere, not just the local WiFi network. The entire system runs locally on the host's machine while remaining accessible globally, providing a perfect balance of simplicity and functionality for casual betting games with friends - and an easy game for robotics enthusiasts.