  Robots need to learn behaviors in intuitive and practical ways for widespread
deployment in human environments. To learn a robot behavior end-to-end, we
train a variant of the ResNet that maps eye-in-hand camera images to
end-effector velocities. In our setup, a human teacher demonstrates the task
via joystick. We show that a simple servoing task can be learned in less than
an hour including data collection, model training and deployment time.
Moreover, 16 minutes of demonstrations were enough for the robot to learn the
task.
