Line Following Robot (LFR)

📌 Project Overview

This project presents the design and implementation of a Line Following Robot (LFR) using Arduino Uno.
The robot is capable of autonomously following a black line on a white surface using a 5-channel IR sensor array.
It can smoothly navigate curves, sharp turns, intersections, and dashed paths using PID-based motor control.

This project was developed as part of the Electronic Shop Practice (ECE 2200) course at Rajshahi University of Engineering & Technology (RUET).

---

🎯 Objectives

• Design and build a functional line-following robot
• Accurately detect and follow black lines
• Execute 45° and 90° turns
• Cross dashed or broken paths
• Implement PWM speed control using Arduino
• Apply PID control for smooth movement
• Gain hands-on experience in robotics and embedded systems

---

🛠️ Hardware Components

• Arduino Uno
• TCRT5000 5-Channel IR Sensor Array
• L298N Motor Driver
• N20 DC Gear Motors (2)
• Rubber Wheels (2)
• Ball Caster
• 3.7V Li-ion Batteries (2)
• Battery Holder
• Switch
• Robot Chassis
• Jumper Wires

---

💻 Software Used

• Arduino IDE
• Programming Language: C / C++

---

⚙️ Working Principle

• IR sensors detect the black line by measuring reflected infrared light.
• Sensor data is processed by the Arduino Uno.
• An error value is calculated based on line deviation.
• A PID control algorithm generates correction signals.
• The L298N motor driver adjusts motor speed and direction using PWM.
• The robot moves forward, turns left/right, or re-centers itself accordingly.

---

🧠 Control Logic

Sensor Pattern	Action
Center detected	Move straight
Left deviation	Turn right
Right deviation	Turn left
No detection	Rotate until line is found

---

📐 Mechanical Design

• Differential drive system with two DC motors
• Ball caster used for balance and stability
• Sensors placed at the front for accurate detection
• Lightweight plywood chassis for strength and portability

---

📊 Results

• Smooth line following on standard tracks
• Accurate turns at intersections
• Stable movement using PWM motor control
• Effective error correction using PID logic

---

⚠️ Limitations

• Sensitive to lighting conditions
• Performance varies on reflective or uneven surfaces
• Limited battery life
• No obstacle detection

---

🚀 Future Improvements

• Obstacle avoidance using ultrasonic sensors
• Wireless monitoring via Bluetooth or WiFi
• LCD or OLED display for real-time data
• Advanced adaptive control algorithms
• Improved power management system

---