Self-Driving Robotic Car

We built a smart vehicle using a Raspberry Pi 4, with PWM for motor control and OpenCV for lane detection, allowing it to autonomously follow lanes and navigate its environment.

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Inspiration

The rapid advancement of technology in smart devices.

What it does

The vehicle uses OpenCV for autonomous navigation by detecting lanes.

How we built it

  • Raspberry Pi 4
  • 4 TT Motors
  • Logitech Webcam
  • OpenCV
  • 5V Battery Pack (to power the L298N module)
  • 5V Portable Battery (to power the Raspberry Pi)
  • L298N motor driver module
  • Soldering wires

Challenges we ran into

  • Limited access to adhesive for securing components.
  • Wires connected to the motor tearing off.
  • Managing and organizing wires efficiently.
  • Tweaking the lane detection for greater precision

Accomplishments that we're proud of

  • Successfully implementing OpenCV for lane detection.
  • Developing a variety of motor functions for vehicle control.
  • Assembling the car from individual components.

What we learned

  • How to arrange motors for optimal performance of motor functions.
  • Efficiently implementing OpenCV lane detection on a Raspberry Pi with limited processing power.
  • Using PWM (Pulse Width Modulation) for precise motor control.

What's next for Self-Driving Robotic Car

  • Adding ultrasonic sensors for object detection.
  • Integrating a TensorFlow Lite model for voice recognition.
  • Upgrading to stronger motors for better performance.
  • Improving the chassis design.
  • Hosting a livestream through the Raspberry Pi.

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