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Designing a Self-Driving Robot

For one of my most exciting projects, I built a self-driving robot using a Raspberry Pi, OpenCV, and a handful of sensors. The goal was to make a robot that could autonomously follow a path, avoid obstacles, and make basic decisions in real time.

The Challenge

Getting a robot to interpret and respond to its environment isn’t easy—especially when it involves real-time decisions and physical hardware. I had to combine image processing, sensor fusion, and motor control into one cohesive system.

Technologies Used

• OpenCV – for detecting lanes and identifying paths through camera input
• Ultrasonic Sensors – to detect and avoid nearby obstacles
• Raspberry Pi – as the central processor running Python scripts
• Motor Drivers & PWM – to adjust speed and direction dynamically

What I Learned

• How to tune vision pipelines for accuracy and speed using OpenCV
• How to calibrate sensor thresholds to avoid false positives
• The importance of isolating problems when debugging hardware issues
• How control logic must adapt in unpredictable physical environments

This project gave me firsthand experience applying computer vision and robotics algorithms to real-world hardware. It was also a great lesson in perseverance—especially when the robot wouldn’t behave the way I expected!

I’m excited to build on this with more autonomous systems and AI-based robotics in the future.