13 December 2024

Autonomous Car Using Raspberry Pi

Create an autonomous car prototype using Raspberry Pi, sensors, and machine learning. This project showcases self-driving car technology, including obstacle detection, lane following, and GPS navigation, all in a compact DIY format.

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dhruvarne22

@dhruvarne22

IoT Projects

Project Details

Autonomous Car Using Raspberry Pi

Introduction

This project involves building a small-scale autonomous car using Raspberry Pi and a variety of sensors. The car will navigate on its own, avoid obstacles, and follow lanes, giving a practical introduction to self-driving technology.

Materials Required

  • Core Components:

    • Raspberry Pi 4 (or any compatible model)
    • Motor driver module (L298N or similar)
    • DC motors with wheels
    • Power bank or battery pack
    • Chassis for the car

  • Sensors:

    • Ultrasonic sensors for obstacle detection
    • Pi Camera or USB webcam for lane following
    • GPS module (optional for navigation)

  • Software:

    • Python with libraries (OpenCV, TensorFlow, etc.)
    • Raspbian OS
    • Pre-trained lane detection and object detection models (optional)

Steps to Build

1. Setting Up Raspberry Pi

  • Install Raspbian OS on an SD card and set up your Raspberry Pi.
  • Enable camera support and install necessary libraries like OpenCV and TensorFlow.

2. Building the Car

  • Assemble the car chassis and attach the DC motors.
  • Connect the motors to the motor driver and link it to the Raspberry Pi GPIO pins.
  • Attach the Pi Camera at the front of the car for lane detection.

3. Adding Sensors

  • Mount ultrasonic sensors at the front and sides for obstacle detection.
  • Connect the sensors to the Raspberry Pi using GPIO pins.

4. Coding the Autonomous Features

  • Write a Python script for:
    • Obstacle detection using ultrasonic sensors.
    • Lane detection using OpenCV and image processing.
    • Optional GPS-based navigation.
  • Use PWM signals to control motor speed and direction based on sensor input.

5. Testing the Car

  • Place the car on a test track with lanes and obstacles.
  • Run the Python script and observe the car's ability to navigate and avoid obstacles.

Challenges and Troubleshooting

  • Fine-tune the lane detection algorithm for different lighting conditions.
  • Adjust the motor speed and sensor sensitivity for smooth operation.
  • Ensure stable power supply to avoid unexpected shutdowns.

Safety Tips

  • Test the car in a controlled environment to avoid damage or accidents.
  • Avoid placing the car on busy roads or dangerous terrains.

Showcase Your Autonomous Car!

  • Use your car as a demonstration of self-driving technology in school or college projects.
  • Enhance the car with features like voice control or real-time data logging.

Project Inspiration

This project offers hands-on experience with robotics and artificial intelligence, drawing inspiration from the advancements in autonomous vehicles.