to mark as completed Fully Autonomous RC Car
In this post I wish to outline the build of a compact indoor autonomous car using neural network for navigation. The setup can be used to train and validate autonomous driving neural network models quickly and easily.
The robot is a two-wheel differential steering type. The robot chassis was laser cut out of 5mm clear acrylic, in order to minimize self-shadowing in front of the camera. As you can see there is no caster wheel, rather balance is via a zip-tie tied in a loop. The usual hardware is present, Raspberry Pi 2 and the Adafruit Motor HAT. A 2200mAh 2S battery piowers the setup. A 3A UBEC is used for stepping down the voltage to drive the Pi and PWM generator.
The robot is loaded with a Raspbian image, and uses the Burro autonomous driving platform to steer and control throttle. Burro uses a pre-trained Convolutional Neural Network model trained using Keras and Tensorflow.
The track is available as a PDF file and can be printed on A0 size paper for best results. The default model included in Burro is suitable for this track.