Over the last few weeks, I built a self-driving car - which essentially is a remote control Rx car that uses a raspberry pi running Python, TensorFlow implementing a end-to-end convolution neural network (CNN)
Of course other than being a bit geeky, I do think this is very cool to help understand and get into some of the basic constructs and mechanics around a number of things - web page design, hardware (maker things), and Artificial Intelligence principles.
There are two different models here - they do use the same ASC and controller that can be programmed. My 3D printer, did mess up a little (my supports were a little off) and which is why you see the top not clean.
The sensor and camera are quite basic, and there is provisions to add and do better over time. The Pi isn’t powerful enough to train the model - you need another machine for that (preferably a I7 core with a GPU). Once trained you can run the model on the Pi for inference.
This is the second car, which is a little different hardware, but the ESC to control the motor and actuators are the same.
The code is simple enough; below is an example of the camera (attached) to the Pi, saving the images it is seeing. Tubs is the location where the images are saved; these can then be transferred to another machine for training or inference.
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Below you can see the car driving itself around the track, where it had to be trained first. The reason it is not driving perfectly is because during training (when I was manually driving it around), I crashed a few times and as a result the training data was messed up. Needed more time to clean that up and retrain it.
This is based on donkey car - which is an open source DIY for platform for small-scale self driving cars. I think it is also perfect to get into with those who have teenagers and a little older kids to get in and experiment. You can read up more details on how to go about building this, and the parts needed here .