In this hands-on project, we bring together various robotic concepts such as line following, obstacle avoidance, and decision making to build a robot that can navigate a maze on its own.
🧭 Maze Design and Navigation Strategy
Understanding typical maze patterns: grid-based, loops, and dead ends
Left-hand and right-hand rule: When to use them and their limitations
Mapping the environment while exploring (basic SLAM implementation)
Deciding whether to backtrack or turn at intersections
🔧 Hardware Setup for Maze Navigation
Using IR or ultrasonic sensors to detect walls and paths
Line sensors to follow floor-based lines if used in the maze
Using encoders or wheel feedback to track movement steps and angles
Importance of tight motor control and speed tuning in narrow paths
🧠 Programming the Robot Brain
Writing logic for decision-making at intersections
Handling loops, dead ends, and open paths with conditional logic
Using arrays or stacks to store visited paths and track movement
Implementing basic recursive or loop-based path discovery algorithms
🚀 Testing and Iteration
Testing with small mazes and gradually increasing complexity
Detecting and fixing logical bugs in movement decisions
Using debugging LEDs or serial prints to understand robot behavior
Recording successful path runs for optimization
By the end of this project, your robot should be able to explore and solve simple mazes using rules and memory. This exercise also lays the foundation for more complex pathfinding and SLAM-based systems you will tackle in future projects.