Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Contextual Reinforcement Learning of Visuo-tactile Multi-fingered
  Grasping Policies   Using simulation to train robot manipulation policies holds the promise of an
almost unlimited amount of training data, generated safely out of harm's way.
One of the key challenges of using simulation, to date, has been to bridge the
reality gap, so that policies trained in simulation can be deployed in the real
world. We explore the reality gap in the context of learning a contextual
policy for multi-fingered robotic grasping. We propose a Grasping Objects
Approach for Tactile (GOAT) robotic hands, learning to overcome the reality gap
problem. In our approach we use human hand motion demonstration to initialize
and reduce the search space for learning. We contextualize our policy with the
bounding cuboid dimensions of the object of interest, which allows the policy
to work on a more flexible representation than directly using an image or point
cloud. Leveraging fingertip touch sensors in the hand allows the policy to
overcome the reduction in geometric information introduced by the coarse
bounding box, as well as pose estimation uncertainty. We show our learned
policy successfully runs on a real robot without any fine tuning, thus bridging
the reality gap.

5
The categories of this paper are: gr-qc
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The categories of this paper are: nucl-ex
29
The categories of this paper are: funct-an
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The categories of this paper are: alg-geom
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The categories of this paper are: nucl-th
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The categories of this paper are: econ
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The categories of this paper are: physics
13
The categories of this paper are: quant-ph
23
The categories of this paper are: solv-int
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The categories of this paper are: astro-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: patt-sol
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The categories of this paper are: chem-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: comp-gas
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The categories of this paper are: q-fin