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Self Driving car using Raspberry Pi and Open CV | Lane Detection | Autonomous Driving
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I embarked on a self-driving car project a few months ago. My initial motivation was to just to put my raspberry pi to some use as it was just lying around for sometime. Little did I know that this endeavor would transform into a captivating journey of discovery and learning.
Throughout this journey, I faced numerous challenges and underwent several iterations, trying out different approaches and designs. It's been a rollercoaster, But I'm thrilled to share that I've finally arrived at a design by 3D printing the car, I successfully obtained a design that now possesses the capability to steer at various angles with precision. Moreover, I implemented a effective approach that utilizes the Hough Transform and Canny edge detection through OpenCV. These techniques have greatly enhanced the car's performance and perception abilities, enabling it to navigate its surroundings more efficiently.
Engaging with robotics has always allowed me to bridge the gap between theory and real-world applications, and this car project is a perfect example of that. Along the way, I acquired valuable knowledge about various image processing techniques and gained insights into the fundamental principles of car localization within an environment. It was fascinating to discover how real-world cars utilize ADAS (Advanced Driver Assistance Systems) features.
Looking ahead, my aim is to improve it further by implementing a deep learning model. The car's newfound capability for autonomous driving allows me to generate essential data for training the model. This opens up a world of exciting possibilities, enabling me to enhance the car's performance and functionality significantly.
#automobile #autonomousdriving #opencv #python #raspberrypi #robotics #selfdriving #machinelearning #deeplearning #robot
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