Line Following Maze Solver

Project Overview

Built for the SRA Lab competition, this intelligent robot combines line-following capabilities with advanced maze-solving algorithms. The robot can navigate complex mazes by following lines while making smart decisions at intersections and dead ends.

Competition Challenge

The SRA Lab maze competition required robots to:

• Follow black lines accurately on white surfaces
• Navigate complex maze patterns with multiple paths
• Make intelligent decisions at intersections
• Handle dead ends and backtrack efficiently
• Find the shortest path to the maze exit
• Complete the course in minimum time

Technical Design

• Line Detection: Array of IR sensors for precise line following
• Maze Mapping: Algorithm to remember visited paths and intersections
• Decision Making: Logic for choosing paths at intersections
• Pathfinding: Implementation of maze-solving algorithms like wall-following
• Motor Control: Precise speed and direction control for smooth navigation

Maze Solving Algorithm

• Left-Hand Rule: Always prefer left turns when multiple options are available
• Dead End Detection: Recognize and backtrack from dead ends efficiently
• Path Memory: Remember visited paths to avoid repeated exploration
• Intersection Mapping: Track all intersection points and their connections
• Optimization: Find shortest path after initial maze exploration

Line Following System

• Sensor Array: Multiple IR sensors for accurate line detection
• PID Control: Smooth and stable line following with minimal oscillation
• Speed Control: Dynamic speed adjustment based on line curvature
• Junction Detection: Identify T-junctions, crossroads, and dead ends
• Error Correction: Quick recovery when robot loses the line

Engineering Challenges

• Sensor Calibration: Fine-tuned IR sensors for consistent line detection under various lighting conditions
• Junction Recognition: Developed robust algorithms to distinguish between different types of intersections
• Path Optimization: Implemented efficient data structures to store and process maze information
• Speed vs Accuracy: Balanced fast movement with reliable line following
• Memory Management: Optimized code for limited microcontroller memory

Competition Achievement

Secured fourth place in the SRA Lab maze-solving competition, demonstrating excellent pathfinding algorithms and reliable sensor integration. The robot successfully navigated complex maze patterns and showed consistent performance across multiple runs.

Key Features

• Accurate line following with PID control
• Intelligent maze-solving algorithms
• Robust junction and dead-end detection
• Path memory and optimization
• Fast and reliable navigation
• Competition-grade performance

Development Journey

• Started with basic line following using simple sensor feedback
• Implemented PID control for smoother line tracking
• Added junction detection and decision-making logic
• Developed maze-solving algorithms and path memory
• Optimized performance through extensive testing and tuning

What I Learned

• Advanced sensor interfacing and calibration
• Pathfinding and maze-solving algorithms
• Real-time embedded systems programming
• PID control implementation and tuning
• Competition robotics strategies
• System optimization under resource constraints

Technical Specifications

• Microcontroller: ESP32 with ESP-IDF framework
• Sensors: Array of IR sensors for line detection
• Motors: DC geared motors with encoder feedback
• Power: Rechargeable Li-Po battery system
• Processing: Real-time control loop at 100Hz
• Memory: Efficient maze mapping data structures

Future Enhancements

• Add computer vision for more robust line detection
• Implement advanced algorithms like A* pathfinding
• Include obstacle avoidance capabilities
• Add wireless communication for remote monitoring
• Develop machine learning for adaptive navigation