Guide: Building an Autonomous Car with Arduino

10.12.2024 - Engine: Gemini

How to Build a Self-Driving Car with Arduino

Hardware Requirements

• Arduino UNO or compatible board
• L298N Dual H-Bridge Motor Driver
• 2 DC Motors
• Ultrasonic Sensors (4-6)
• Infrared Sensors (2)
• Steering Servo
• Power Source (e.g., 9V Battery)
• Chassis or platform

Programming

Arduino IDE Script

// Import libraries
#include <Arduino.h>
#include <L298N.h>

// Define constants
#define MOTOR_A_PIN 1
#define MOTOR_B_PIN 2
#define MOTOR_ENABLE_PIN 3

// Create motor object
L298N motor(MOTOR_ENABLE_PIN, MOTOR_A_PIN, MOTOR_B_PIN);

// Declare variables
int leftSensor = A0;
int rightSensor = A1;
int frontSensor = A2;

// Setup function
void setup() {
  // Configure sensors as inputs
  pinMode(leftSensor, INPUT);
  pinMode(rightSensor, INPUT);
  pinMode(frontSensor, INPUT);

  // Set motor speed
  motor.setSpeed(150);
}

// Loop function
void loop() {
  // Read sensor data
  int leftValue = analogRead(leftSensor);
  int rightValue = analogRead(rightSensor);
  int frontValue = analogRead(frontSensor);

  // Obstacle detected?
  if (frontValue < 100) {
    // Stop
    motor.stop();
  } else {
    // Drive
    if (leftValue > rightValue) {
      // Steer right
      motor.forward();
      motor.left();
    } else if (leftValue < rightValue) {
      // Steer left
      motor.forward();
      motor.right();
    } else {
      // Drive straight
      motor.forward();
    }
  }
}

Challenges

• Object detection: The car must be able to detect obstacles in its environment.
• Path planning: The car must determine an optimal path based on sensor data.
• Sensor fusion: Data from multiple sensors needs to be combined to create an accurate picture of the environment.
• Calibration: Sensors need to be calibrated for different lighting conditions and environments.
• Error handling: The car must be able to respond to unexpected events such as disruptions or obstacles.

Tips

• Start with a simple course and gradually add more complex obstacles.
• Use high-quality sensors and calibrate them regularly.
• Implement an obstacle avoidance algorithm that takes into account data from multiple sensors.
• Test the car in different environments and weather conditions.
• Be patient and be prepared to improve and adapt the car over time.