A micromouse-style learning build with wall sensors, encoder odometry, cell mapping, turn calibration and a safe speed ramp.
A maze-solving robot is a step beyond line following because the robot must sense walls, estimate position and remember decisions. The first goal is not speed; it is repeatable turns and a map that matches the maze.
Build a small test maze, log sensor readings and calibrate one cell at a time. After it can explore slowly, add flood-fill or another path planner and only then increase speed.
Compact enough for maze cells
Distance and turn feedback
Wall distance and openings
Fast control loop and map memory
Smooth low-speed turns
Repeatable test environment
Start with left-hand or right-hand rules before mapping.
Explore cells, score distances and run the shortest path.
Add acceleration profiles after turns are repeatable.
Treat the generated output as a prototype plan, not a certified product. Body-adjacent, high-voltage, optical-energy and mobility builds need qualified review before real-world use.
For a slow large maze, yes. Small mazes are easier with ToF sensors.
Wall following is easiest. Flood-fill is a good next step for micromouse style mazes.
Wheel slip, bad turn calibration and inconsistent wall thresholds are common causes.
Core path for choosing a robot project and avoiding common beginner mistakes.
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Start with this prompt prefilled, then let RoboHub generate the live parts list, wiring plan, CAD and firmware.
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