Abstract: This paper aims to show that robots equipped with a vision-based tactile
sensor can perform dynamic manipulation tasks without prior knowledge of all
the physical attributes of the objects to be manipulated. For this purpose, a
robotic system is presented that is able to swing up poles of different masses,
radii and lengths, to an angle of 180 degrees, while relying solely on the
feedback provided by the tactile sensor. This is achieved by developing a novel
simulator that accurately models the interaction of a pole with the soft
sensor. A feedback policy that is conditioned on a sensory observation history,
and which has no prior knowledge of the physical features of the pole, is then
learned in the aforementioned simulation. When evaluated on the physical
system, the policy is able to swing up a wide range of poles that differ
significantly in their physical attributes without further adaptation. To the
authors' knowledge, this is the first work where a feedback policy from
high-dimensional tactile observations is used to control the swing-up
manipulation of poles in closed-loop.
Authors: Thomas Bi, Carmelo Sferrazza, Raffaello D'Andrea (ETH Zurich)