Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Pixels to Plans: Learning Non-Prehensile Manipulation by Imitating a
  Planner   We present a novel method enabling robots to quickly learn to manipulate
objects by leveraging a motion planner to generate "expert" training
trajectories from a small amount of human-labeled data. In contrast to the
traditional sense-plan-act cycle, we propose a deep learning architecture and
training regimen called PtPNet that can estimate effective end-effector
trajectories for manipulation directly from a single RGB-D image of an object.
Additionally, we present a data collection and augmentation pipeline that
enables the automatic generation of large numbers (millions) of training image
and trajectory examples with almost no human labeling effort.
  We demonstrate our approach in a non-prehensile tool-based manipulation task,
specifically picking up shoes with a hook. In hardware experiments, PtPNet
generates motion plans (open-loop trajectories) that reliably (89% success over
189 trials) pick up four very different shoes from a range of positions and
orientations, and reliably picks up a shoe it has never seen before. Compared
with a traditional sense-plan-act paradigm, our system has the advantages of
operating on sparse information (single RGB-D frame), producing high-quality
trajectories much faster than the "expert" planner (300ms versus several
seconds), and generalizing effectively to previously unseen shoes.

21
The categories of this paper are: adap-org
22
The categories of this paper are: chao-dyn
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
12
The categories of this paper are: nucl-th
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
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The categories of this paper are: bayes-an
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The categories of this paper are: supr-con
11
The categories of this paper are: hep-lat
3
The categories of this paper are: physics
34
The categories of this paper are: chem-ph
31
The categories of this paper are: ao-sci
17
The categories of this paper are: q-fin