Maze-Solving Robot (Micromouse-Inspired)

Table of Contents

• Introduction
• Features
• Hardware Components
• Algorithm
• Installation & Usage
• Project Team
• References

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Introduction

This project presents a maze-solving robot inspired by the Micromouse competition. The robot autonomously navigates and solves mazes using an optimized flood-fill algorithm, tracing the shortest path from start to target in minimum time. The robot logic is implemented in C++ and runs on an Arduino Nano microcontroller, interfacing with infrared sensors and encoder motors for real-time navigation and wall detection.

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Features

• Shortest path tracing using optimized flood-fill algorithm and from start to target.
• Real-time wall detection with three GP2Y0A41SK0F infrared sensors.
• Precise movement control using encoder motors and PID control
• Custom double-layer PCB designed for compact integration
• EEPROM-based map storage for persistent maze data
• 3D-printed PLA chassis for lightweight and robust structure
• Dynamic path replanning for real-time recovery from new obstacles or sensor inconsistencies

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Hardware Components

• Microcontroller: Arduino Nano (ATmega328)
• Sensors: 3× GP2Y0A41SK0F sharp infrared sensors
• Motors: 2× N20 6V 500 RPM Encoder Motors
• Motor Driver: TA6586 Dual H-Bridge
• Battery: 2× 3.7V 1250mAh LiPo cells (in series)
• Wheels: N20 motor rubber small wheels
• Castor Wheel: N20 castor robot ball wheel
• Custom PCB: Fabricated along with from scratch designing Arduino Nano on EasyEDA, integrating all components

  - With Scratch Arduino Nano - PCB\Gerber_Scratch_nano.zip
  - Assembeled Arduino Nano - PCB\Gerber_to_assemble_nano.zip
  

• Custom Chassis: Designed with Solidworks, and with PolyLactic Acid

  CAD\Assem11 - Copy.SLDASM
  

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Algorithm

• Flood-Fill Algorithm: Optimized for speed and efficiency, with comparison to standard flood-fill for performance gains
• Wall following Algorithm: Tried Basic wall following algorithm based on breadth first search.
• PID Control: Utilizes motor encoder feedback for precise motor control and accurate positioning
• Wall Detection: Real-time distance calculation and alignment using IR sensors
• EEPROM Storage: Maze mapping data stored and updated in Arduino Nano’s EEPROM (1 KB)
• Reset Capability: EEPROM data can be reset for new maze runs

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Installation & Usage

1. Wiring: Connect components as per the circuit diagram.
2. Programming: Upload the C++ code to the Arduino Nano using Arduino IDE.

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Project Team

• Prof. Soumya Bagchi – Assistant Professor, Department of Physics, IIT ISM Dhanbad
• Palak Kumari – Computer Science & Engineering
• Prasoon Krishna Yadav – Electronics and Communication Engineering
• Prayag Asrani – Mechanical Engineering
• Pratyush Tripathi – Electrical Engineering
• Abhirup Choudhury – Mathematics and Computing

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References

1. Micromouse History
2. Monk, S. (2012). Programming Arduino: Getting Started with Sketches. McGraw-Hill Education.
3. Arduino Nano Datasheet
4. IEEE Micromouse History
5. Micromouse Maze Solving Algorithm (IEEE)
6. Nishi, T., & Yasuda, T. (1990). A study on algorithms for Micromouse competitions. Robotics and Automation Journal.
7. Elger, D. (1987). Wall-Following Algorithms for Autonomous Robots. Control Systems Magazine.
8. Brooks, R. A. (1986). A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation.
9. Arduino Nano Board Information
10. Arduino Nano Pinout
11. TA6586 Motor Driver Datasheet
12. GP2Y0A41SK0F IR Sensor Datasheet
13. Arduino Nano Schematics
14. Arduino Nano Eagle File
15. Flood Fill Algorithm Comparison

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For more details, see the full project report and source files in this repository.