Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Towards Lifelong Self-Supervision: A Deep Learning Direction for
  Robotics   Despite outstanding success in vision amongst other domains, many of the
recent deep learning approaches have evident drawbacks for robots. This
manuscript surveys recent work in the literature that pertain to applying deep
learning systems to the robotics domain, either as means of estimation or as a
tool to resolve motor commands directly from raw percepts. These recent
advances are only a piece to the puzzle. We suggest that deep learning as a
tool alone is insufficient in building a unified framework to acquire general
intelligence. For this reason, we complement our survey with insights from
cognitive development and refer to ideas from classical control theory,
producing an integrated direction for a lifelong learning architecture.

16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg
30
The categories of this paper are: q-alg
15
The categories of this paper are: nucl-ex
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
17
The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
22
The categories of this paper are: chao-dyn
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th