Embedded Maze-Solving Robot

Overview

This project involves designing and implementing a maze-solving robot using an Arduino Uno microcontroller and an infrared (IR) sensor. The robot is capable of detecting and following a black line on a white surface, utilizing the Left-Hand-Rule (LHR) algorithm to navigate and solve mazes effectively.

Technologies Used

• Arduino Uno: The central microcontroller for controlling the robot and processing sensor data.
• Infrared (IR) Sensor: Used to detect the black line on the white surface and ensure the robot stays on the path.
• Left-Hand-Rule (LHR) Algorithm: An algorithm for maze solving that guides the robot through the maze by always keeping its left hand (or sensor) in contact with the wall.

Features

1. Line Detection: The IR sensor continuously scans the surface to detect the black line and keep the robot on track.
2. Maze Navigation:
   • Left-Hand-Rule (LHR) Algorithm: The robot follows the LHR algorithm, making decisions at intersections and turns to navigate the maze.
   • Obstacle Detection: The IR sensor also helps in detecting walls and obstacles, ensuring the robot makes appropriate turns to avoid collisions.
3. Autonomous Operation: Once placed at the maze entrance, the robot autonomously navigates and solves the maze without any human intervention.
4. Real-time Processing: The Arduino Uno processes sensor data in real-time, making immediate decisions to navigate the maze efficiently.

Implementation

1. Hardware Setup:

   • Arduino Uno: Acts as the brain of the robot, controlling motors and processing input from the IR sensor.
   • IR Sensor: Mounted on the robot to detect the black line and guide the robot along the path.
   • Motors and Wheels: Enable the robot to move forward, backward, and turn based on the signals from the Arduino.

2. Algorithm Execution:

   • Line Following: The IR sensor detects the black line, and the Arduino adjusts the motors to keep the robot on track.
   • LHR Algorithm: At each intersection or turn, the robot decides its direction based on the LHR algorithm, ensuring it explores all paths to find the maze exit.

3. Coding and Programming:

   • Arduino IDE: Used to write and upload the code to the Arduino Uno.
   • Sensor Calibration: Ensuring the IR sensor accurately distinguishes between the black line and white surface.

Benefits

• Autonomous Navigation: The robot operates independently, requiring no human intervention once started.
• Educational Value: Provides a hands-on learning experience in embedded systems, robotics, and algorithm implementation.
• Practical Application: Can be adapted for various real-world applications such as automated floor cleaning, pathfinding robots, and more.

Future Enhancements

• Advanced Algorithms: Implement more sophisticated algorithms like Dijkstra's for faster and more efficient maze-solving.
• Sensor Integration: Add additional sensors (e.g., ultrasonic sensors) for better obstacle detection and navigation.
• Customization: Allow users to set custom maze parameters and robot behaviors through a user interface.