To operate successfully in the unstructured environment of homes and small businesses, robots will be implemented by unskilled operators who cannot explicitly program their motions. Recently, imitation learning has been used to train robots that manipulate their environment based on pixel-to-action control. The robot actions are determined by camera inputs without programmed trajectories. Such training is often performed on robotic hardware which was not designed for imitation learning. This paper describes a new robot which is designed expressly to improve the training speed and ability of pixel-to-action policies. In particular, hexapod robot hardware is designed for teleoperation, thus improving correspondence and simplifying human control.
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