Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Third-Person Visual Imitation Learning via Decoupled Hierarchical
  Controller   We study a generalized setup for learning from demonstration to build an
agent that can manipulate novel objects in unseen scenarios by looking at only
a single video of human demonstration from a third-person perspective. To
accomplish this goal, our agent should not only learn to understand the intent
of the demonstrated third-person video in its context but also perform the
intended task in its environment configuration. Our central insight is to
enforce this structure explicitly during learning by decoupling what to achieve
(intended task) from how to perform it (controller). We propose a hierarchical
setup where a high-level module learns to generate a series of first-person
sub-goals conditioned on the third-person video demonstration, and a low-level
controller predicts the actions to achieve those sub-goals. Our agent acts from
raw image observations without any access to the full state information. We
show results on a real robotic platform using Baxter for the manipulation tasks
of pouring and placing objects in a box. Project video and code are at
https://pathak22.github.io/hierarchical-imitation/

0
The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
19
The categories of this paper are: eess
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
29
The categories of this paper are: funct-an
2
The categories of this paper are: math
5
The categories of this paper are: gr-qc
33
The categories of this paper are: plasm-ph