Team Vegavath · Robotics

Maze Solver

An 8x8 autonomous maze-solving robot by Vega Vath Racing. Pick a start and goal, choose the robot's starting heading, and watch it find the shortest route.

(0, 0)(1, 0)(2, 0)(3, 0)(4, 0)(5, 0)(6, 0)(7, 0)(0, 1)(1, 1)(2, 1)(3, 1)(4, 1)(5, 1)(6, 1)(7, 1)(0, 2)(1, 2)(2, 2)(3, 2)(4, 2)(5, 2)(6, 2)(7, 2)(0, 3)(1, 3)(2, 3)(3, 3)(4, 3)(5, 3)(6, 3)(7, 3)(0, 4)(1, 4)(2, 4)(3, 4)(4, 4)(5, 4)(6, 4)(7, 4)(0, 5)(1, 5)(2, 5)(3, 5)(4, 5)(5, 5)(6, 5)(7, 5)(0, 6)(1, 6)(2, 6)(3, 6)(4, 6)(5, 6)(6, 6)(7, 6)(0, 7)(1, 7)(2, 7)(3, 7)(4, 7)(5, 7)(6, 7)(7, 7)
START: (0, 0)GOAL: (7, 7)
Start heading
READY

How it works

This page works from the known map of the competition maze. A breadth-first search computes the shortest route between the start and goal you pick, then converts that route into the exact turn-by-turn commands the robot would execute from its starting heading. Because the map is known ahead of time, the route shown here is genuinely the shortest one, not a guess refined over several runs.

The physical robot

ControllerArduino Uno
Heading / turnsMPU6050 IMU
Front sensorHC-SR04 -- wall detection and safety
Side sensorsLeft + right HC-SR04 -- wall sensing and corridor centering
DistanceRight-motor encoder
Motor driverTB6612FNG

The robot does not blindly trust motion timing. Even while executing a route it already knows from the map, it keeps verifying its surroundings with its sensors, correcting its heading with the IMU and its distance with the encoder rather than assuming a fixed number of milliseconds equals one cell.

Planned autonomous mode

A second mode is planned separately: instead of being handed the map, the robot would build and maintain its own maze state onboard and run flood-fill replanning as it discovers walls, updating its route on the fly. That discovery mode is a distinct piece of work from the known-map shortest-route solver shown on this page.