Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning visual servo policies via planner cloning   Learning control policies for visual servoing in novel environments is an
important problem. However, standard model-free policy learning methods are
slow. This paper explores planner cloning: using behavior cloning to learn
policies that mimic the behavior of a full-state motion planner in simulation.
We propose Penalized Q Cloning (PQC), a new behavior cloning algorithm. We show
that it outperforms several baselines and ablations on some challenging
problems involving visual servoing in novel environments while avoiding
obstacles. Finally, we demonstrate that these policies can be transferred
effectively onto a real robotic platform, achieving approximately an 87%
success rate both in simulation and on a real robot.

27
The categories of this paper are: comp-gas
29
The categories of this paper are: funct-an
19
The categories of this paper are: eess
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
2
The categories of this paper are: math
26
The categories of this paper are: bayes-an
15
The categories of this paper are: nucl-ex
5
The categories of this paper are: gr-qc
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
10
The categories of this paper are: q-bio
16
The categories of this paper are: stat
31
The categories of this paper are: ao-sci