Building a Line-Following Robot

Table of Contents🔗

• Introduction
• Components Needed
• Working Principle
• Circuit Assembly
• Programming Logic
• Testing and Calibration
• Advanced Enhancements
• Conclusion

Introduction🔗

Line-following robots detect and follow a contrasting path using infrared (IR) sensors, making them perfect for learning automation and control systems. These robots are widely used in industries for material transport and in education to teach robotics fundamentals. This project combines electronics, coding, and mechanical design, providing a holistic introduction to robotics.

Components Needed🔗

• Use at least 3 IR sensors for accurate path detection.
• A 9V battery powers the motor driver separately to prevent voltage drops.
• Choose a rigid chassis for stability.

Working Principle🔗

Sensor-Based Navigation

IR sensors emit infrared light and measure reflected intensity:

• High reflection (light surface): Sensor outputs LOW.
• Low reflection (dark line): Sensor outputs HIGH.

Sensors are arranged linearly to detect deviations from the path. For example:

• Left sensor HIGH: Robot steers right.
• Right sensor HIGH: Robot steers left.

Control Algorithms

• Threshold-Based Control: Simple on/off adjustments based on sensor readings.
• PID Control: Advanced method using Proportional-Integral-Derivative terms to minimize overshooting and oscillations.

Circuit Assembly🔗

Step 1: Sensor Connections

1. Connect VCC and GND of each TCRT5000 to Arduino’s 5V and GND.

2. Wire sensor OUT pins to digital/analog pins (e.g., D2, D3, D4 or A0-A2).

Step 2: Motor Driver Setup

1. Link IN1-IN4 of the L298N to Arduino pins (e.g., D5-D8).

2. Connect motors to driver outputs (OUT1-OUT4).

3. Power the driver with a 9V battery (separate from Arduino).

• Use a common ground for all components.
• Add decoupling capacitors to reduce electrical noise.

Programming Logic🔗

Sensor Calibration

Read sensor values via the Serial Monitor to determine thresholds for line vs. background:

void setup() {
  Serial.begin(9600);
  pinMode(IR_SENSOR_LEFT, INPUT);
  pinMode(IR_SENSOR_CENTER, INPUT);
  pinMode(IR_SENSOR_RIGHT, INPUT);
}
void loop() {
  Serial.print("Left: "); Serial.print(analogRead(A0));
  Serial.print(" | Center: "); Serial.print(analogRead(A1));
  Serial.print(" | Right: "); Serial.println(analogRead(A2));
  delay(200);
}

Basic Proportional Control

Adjust motor speeds based on error:

int error, lastError = 0;
float Kp = 0.5;  // Proportional gain
void loop() {
  int leftVal = digitalRead(IR_SENSOR_LEFT);
  int centerVal = digitalRead(IR_SENSOR_CENTER);
  int rightVal = digitalRead(IR_SENSOR_RIGHT);
  // Calculate error (e.g., -1=left, 0=centered, +1=right)
  error = (leftVal == HIGH) ? -1 : (rightVal == HIGH) ? 1 : 0;
  int adjust = Kp * error;
  setMotors(baseSpeed - adjust, baseSpeed + adjust);
}

Full PID Implementation

Add integral and derivative terms for precision:

float Kp = 0.5, Ki = 0.01, Kd = 0.1;
int integral = 0, derivative = 0, lastError = 0;
void loop() {
  int error = calculateError();  // Custom function based on sensor readings
  integral += error;
  derivative = error - lastError;
  int adjust = (Kp * error) + (Ki * integral) + (Kd * derivative);
  setMotors(baseSpeed - adjust, baseSpeed + adjust);
  lastError = error;
}

Testing and Calibration🔗

1. Sensor Calibration:

• Print sensor values over light/dark surfaces.
• Set a threshold (e.g., 500 for analog sensors).

2. PID Tuning:

• Start with Kp; increase until slight oscillation occurs.
• Introduce Kd to dampen overshooting.
• Use Ki sparingly to correct drift.

3. Track Testing:

• Use electrical tape on a white surface for initial tests.
• Gradually increase speed after successful low-speed runs.

Advanced Enhancements🔗

• Wireless Control: Integrate an HC-05 Bluetooth module for remote mode switching.
• Speed Encoders: Add rotary encoders to monitor wheel speed.
• OLED Display: Show real-time sensor data and PID values.
• Obstacle Avoidance: Use an ultrasonic sensor to pause movement when blocked.
• Auto-Calibration: Implement startup routines to adapt to lighting conditions.

Conclusion🔗

Building a line-following robot with Arduino teaches critical skills in robotics, from sensor integration to PID tuning. By experimenting with sensor placement, track design, and control parameters, you can create a robot capable of navigating complex paths. Whether for education, competition, or industrial prototyping, this project offers endless opportunities for innovation. Ready to race? 🏁