Robot Tour

Category: Technology & Engineering

Format: Build

Participants: 2

What It Is

Robot Tour is an autonomous robotics event. Teams pre-design, build, and program a wheeled robotic vehicle to navigate a defined course, stop precisely at designated waypoints, and interact with a water bottle target — all without any human input during the run. The robot must operate fully autonomously using sensors, not AI or machine learning.

What to Know

Robotics & Control:

• Microcontrollers: Arduino Uno/Mega, Raspberry Pi Pico, or similar embedded platforms
• Motor control: DC motors with PWM speed control, servo motors for steering
• Differential drive: most common robot drivetrain — two independently driven wheels for steering
• Dead reckoning: using time + speed (or encoder counts) to estimate position/distance traveled
• PID control: proportional-integral-derivative feedback loops for smooth, accurate motion

Sensors (allowed):

• Ultrasonic distance sensors (e.g., HC-SR04): detect the water bottle target distance
• Wheel encoders: optical or magnetic, measure rotation for precise distance control
• IR sensors: line following or proximity detection
• IMU / gyroscope: heading/orientation tracking for turns
• Note: Cameras and laser sensors are explicitly prohibited by rules

Programming:

• State machine design: define states (moving, stopped at waypoint, interacting with target)
• Sequence control: timing each leg of the course
• Waypoint logic: stopping accurately at each designated point
• Target interaction: using ultrasonic sensor to detect water bottle proximity
• No AI or machine learning allowed in any part of the code

Mechanical Design:

• Chassis rigidity: prevent flex that causes inconsistent straight-line travel
• Wheel traction and alignment
• Sensor mounting: ultrasonic sensor placement for reliable target detection
• Cable management: loose wires cause competition-day failures

Competition Format

The course is revealed at competition (or shortly before). The robot is placed at the start, powered on, and must autonomously navigate the course, pausing at each waypoint for a defined time, and interact with the water bottle target (e.g., stop within a specified distance). Scoring rewards accuracy at waypoints and correct target interaction. Human intervention after the run starts results in penalties.

Notes

• AI/ML policy: No AI or machine learning algorithms allowed. Cameras prohibited. Lasers prohibited.
• Ultrasonic sensors are the primary tool for target detection — practice reliable bottle detection at various distances.
• Build in adjustable timing/encoder constants so you can calibrate quickly on competition day for the specific course dimensions.
• Test on multiple floor surfaces — tile, carpet, and wood behave differently for traction and thus distance accuracy.
• Waypoint stopping accuracy is often the primary scoring differentiator among top teams.
• Have a backup plan if the ultrasonic sensor misfires — a timed fallback that still stops near the target is better than no interaction.
• Practice full run-throughs as a team: one member programs, one handles hardware checks and calibration.