I would share my this project related to JetBot and JetRacer. My Project is learning_racer that can AI agent using deep reinforcement learning.
This software can learning policy of driving JetBot or JetRacer without human teaching(unsupervised learning) in 10 to 15 minutes.
This agent can run on the Jetson Nano. Why can run on Jetson Nano and short learning time? because using integrate of SAC[soft actor critic] and VAE. SAC is a state of the art off-policy reinforcement learning method.
In addition VAE train on cloud server beforehand as CNN layer of SAC.(This method called state representation learning) .
Detail of SAC here:
This implementation is based upon greate work of Antonin RAFFIN:
you can setup the software to JetBot(JetPack4.2<=) and JetRacer(JetCard based) using install shell easily. likely:
$ cd ~/ && git clone https://github.com/masato-ka/airc-rl-agent.git $ cd airc-rl-agent $ sh install_jetpack.sh
My project page in here :
You can see demo in here: