Early results from my AI training runs. I've trained my $200 robot arm on a simple picking task using imitation learning. It has learned to control the robot arm using only camera images and joint states.
The learning algorithm is based on ACT from @tonyzzhao. However, it is modified to use language instructions to learn multiple tasks with a single neural network.
The video shows a policy that was trained on two instructions. One instruction to pick up the block and one to put it down. The entire training dataset contains about 400s of teleoperated trajectories.