Go-kart ditches expensive sensors for a single camera to achieve "autonomous" driving

Austin Blake, a YouTuber, transformed his homemade go-kart, dubbed 'Crazy Cart,' into a self-driving platform by utilizing just a single camera. He created a track using contrasting tape in his workshop and recorded 15,000 images of the kart on the track as part of a process called behavioral cloning via a neural network.

Initially, Blake faced difficulties as the network struggled to distinguish track edges and navigate sharp turns. However, his breakthrough came when he enhanced track visibility with bright blue tape, improving the model's accuracy to autonomously maneuver using only monocular vision.

Though Blake's project is limited to a constrained environment as opposed to public roads, it effectively demonstrates machine learning's capability to derive driving intelligence. Utilizing three Arduinos, one for steering predictions, another for motor control, and a third for throttle, Blake's project showcases a resourceful approach to self-driving technology on a shoestring budget.